Регистрация

Поиск скриптов по запросу "stop loss"

High-Probability Entry System by Dahhans,DfirstX🎯 WHAT IT DOES This indicator combines 4 different factors to identify high-probability trade entries. It only shows a signal when ALL conditions align, filtering out weak setups. 🔧 HOW IT WORKS (4 FACTORS) | Factor | What It Measures | Long Signal | Short Signal | | --------------- | --------------------- | ---------------------------- | -------------------------------- | | 1. Trend | Price vs 50 EMA | Price > 50 EMA ✅ | Price < 50 EMA ✅ | | 2. EMA Cross | 9 EMA crossing 21 EMA | 9 crosses ABOVE 21 ✅ | 9 crosses BELOW 21 ✅ | | 3. RSI Momentum | RSI direction | RSI turning UP from oversold | RSI turning DOWN from overbought | | 4. Confirmation | Price vs both EMAs | Price > both EMAs | Price < both EMAs | 📈 VISUALS | Visual | Meaning | | ---------------- | --------------------------------------------- | | Green Background | Uptrend (price above 50 EMA) | | Red Background | Downtrend (price below 50 EMA) | | BUY Label | All 4 conditions met - high probability long | | SELL Label | All 4 conditions met - high probability short | | Red Line | Stop loss level | | Blue Line | 9 EMA (fast) | | Red Line | 21 EMA (slow) | | Orange Line | 50 EMA (trend) | 🎯 SCORE SYSTEM (0-4) | Score | Meaning | | ----- | -------------------------------------- | | 4/4 | Perfect alignment - HIGH probability | | 3/4 | Strong setup - good to trade | | 2/4 | Weak setup - avoid or smaller position | | 0-1/4 | No trade | Only trade when score is 3 or 4. 🛑 RISK MANAGEMENT • Stop Loss: Automatically calculated using ATR (2x ATR below entry for longs) • Position Sizing: Risk 1-2% per trade • Never trade against the trend ⚠️ WHEN IT FAILS | Market Condition | Why It Fails | | ---------------- | ------------------------------------ | | Sideways/Choppy | EMA crosses but no trend | | Low Volume | Signals but no follow-through | | News Events | Gap moves skip stop loss | | Over-optimized | Works on historical data, not future | 📋 EXAMPLE TRADE BTC at $67,000 ├── Price > 50 EMA ($65,000) ✅ TREND ├── 9 EMA crosses above 21 EMA ✅ CROSS ├── RSI turning up from 35 ✅ MOMENTUM └── Price > both EMAs ✅ CONFIRMATION RESULT: BUY signal at $67,000 STOP: $64,500 (2x ATR) TARGET: $70,000+ 🎯 BEST TIMEFRAMES | Timeframe | Quality | | --------- | -------------------------------- | | Daily | Best signals (less noise) | | 4H | Good balance | | 1H | More signals, more false signals | 📚 KEY CONCEPTS USED | Concept | Explanation | | ------------- | ------------------------------------------------------ | | EMA (9/21/50) | Moving averages - 9 is fast, 21 is medium, 50 is trend | | RSI | Momentum oscillator - measures overbought/oversold | | ATR | Volatility measure - used for stop loss | | Confluence | Multiple factors agreeing = higher probability | This indicator is designed to filter out noise and only show you trades when the odds are in your favor.
Индикатор Pine Script®
от dahhan1996
Precision Pivot Confluence Engine [JOAT]Precision Pivot Confluence Engine Introduction The Precision Pivot Confluence Engine is an open-source technical indicator that combines Central Pivot Range (CPR) analysis with Smart Money Concepts (SMC), multi-oscillator divergence detection, and institutional order flow patterns. This mashup integrates multiple proven methodologies into a unified confluence system designed to identify high-probability trading zones where institutional and retail liquidity intersect. The indicator is built for traders who understand that no single signal provides consistent edge, but multiple confirming factors working together can significantly improve trade selection. By synthesizing CPR levels, Fair Value Gaps, Order Blocks, liquidity sweeps, and divergence patterns, this tool helps identify structural market inflection points. Chart showing CPR levels, FVG zones, Order Blocks, and divergence signals on 4H timeframe Why This Mashup Exists This indicator combines five distinct analytical frameworks that complement each other: CPR Analysis: Identifies key pivot levels where institutional algorithms and retail traders make decisions Smart Money Concepts: Tracks Fair Value Gaps, Order Blocks, and Breaker Blocks showing institutional positioning Divergence Detection: Uses RSI, MACD, and Stochastic RSI to identify momentum exhaustion Liquidity Analysis: Detects liquidity sweeps where stop hunts occur before reversals Volume Confirmation: Validates moves with volume analysis and delta calculations Each component addresses a different aspect of market structure. CPR provides static reference levels, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity sweeps identify stop hunts, and volume confirms genuine moves versus noise. Together, they create a multi-dimensional view of market conditions. Core Components Explained 1. Enhanced CPR System The Central Pivot Range system calculates Daily and Weekly pivot levels using the formula: Pivot = (High + Low + Close) / 3 BC (Bottom Central) = (High + Low) / 2 TC (Top Central) = (Pivot - BC) + Pivot The indicator analyzes CPR width to determine market regime: Narrow CPR (width < 0.5%): Indicates compression and potential breakout conditions Wide CPR (width > 1.5%): Suggests ranging market with less directional conviction Price position relative to CPR: Above both Daily and Weekly pivots = bullish structure, below = bearish structure CPR levels act as magnetic zones where price tends to react. The indicator tracks distance from pivots to identify overextension and mean reversion opportunities. 2. Smart Money Concepts Integration Fair Value Gaps (FVG): Bullish FVG occurs when current low > high from 2 bars ago, leaving an unfilled gap Bearish FVG occurs when current high < low from 2 bars ago The indicator calculates FVG size as percentage of price and filters for significant gaps (> 0.3%) to avoid noise. FVGs represent inefficient price delivery where institutions moved price quickly, often returning to fill these gaps later. Order Blocks (OB): Bullish OB: Two consecutive bearish candles followed by strong bullish candle with high volume Bearish OB: Two consecutive bullish candles followed by strong bearish candle with high volume Order Blocks mark the last opposite-direction move before a strong impulse, indicating where institutions accumulated or distributed positions. Breaker Blocks: Failed Order Blocks that get violated become Breaker Blocks, signaling potential trend reversal. The indicator tracks the last bullish and bearish OB levels and alerts when price breaks through them. Liquidity Sweeps: The indicator identifies when price briefly exceeds recent highs/lows (20-bar lookback) but closes back inside the range. These "stop hunts" often precede reversals as institutions trigger retail stops before moving price in the intended direction. Example showing FVG zones, Order Blocks, and liquidity sweep markers 3. Multi-Oscillator Divergence System The indicator simultaneously tracks divergences across three oscillators: RSI Divergence: Bullish: Price makes lower low, RSI makes higher low (momentum improving despite price weakness) Bearish: Price makes higher high, RSI makes lower high (momentum deteriorating despite price strength) MACD Divergence: Tracks histogram divergences using the same pivot-based logic Stochastic RSI Divergence: More sensitive than RSI, catches early momentum shifts The indicator uses a 5-bar pivot lookback to identify swing highs/lows and compares current pivots with previous pivots to detect divergences. When multiple oscillators show divergence simultaneously, it signals strong momentum exhaustion. 4. Volume Analysis Engine Volume MA Comparison: Identifies high volume (> 1.5x MA) and climax volume (> 3x MA) Volume Delta: Cumulative difference between buying volume (green candles) and selling volume (red candles) Delta Trend: Compares current delta to 20-period MA to identify institutional accumulation or distribution Volume Confirmation: Validates bullish moves with high volume + rising delta, bearish moves with high volume + falling delta 5. Confluence Scoring System The indicator calculates a real-time confluence score (0-100) by weighting each component: Confluence Score Components: - CPR Position: Up to 15 points (bullish above pivots, bearish below) - SMC Signals: Up to 10 points (FVG + OB + Breaker + Liquidity Sweeps) - Divergence: Up to 10 points (single oscillator = 5, multiple = 10) - Volume: Up to 10 points (confirmed volume = 7, climax = additional 3) - Trend Alignment: Up to 5 points (price vs key MAs) Scores above 70 indicate strong confluence for potential trades. The dashboard displays individual component scores for transparency. Visual Elements CPR Lines: Daily Pivot (yellow), TC/BC (yellow transparent), Weekly Pivot (yellow circles) FVG Boxes: Green boxes for bullish FVGs, red boxes for bearish FVGs Order Block Boxes: Solid green/red boxes marking institutional zones Breaker Block Labels: "BB" markers when Order Blocks fail Liquidity Sweep Labels: "LIQ" and "STRONG LIQ" positioned at sweep tips Divergence Labels: "D" markers at divergence pivot points Dashboard: Top-right table showing confluence score and component breakdown How Components Work Together The mashup creates a layered analysis approach: Layer 1 - Structure: CPR levels define key zones where reactions are likely Layer 2 - Institutional Behavior: SMC concepts show where smart money is positioned Layer 3 - Momentum: Divergences indicate when current trend is losing steam Layer 4 - Confirmation: Volume validates whether moves are genuine or false Layer 5 - Synthesis: Confluence score combines all factors into actionable signal Example scenario: Price approaches Daily Pivot (Layer 1) where a bullish Order Block exists (Layer 2), RSI shows bullish divergence (Layer 3), and volume delta is rising (Layer 4). The confluence score jumps to 85 (Layer 5), signaling high-probability long setup. Input Parameters CPR Settings: Show Daily CPR: Toggle daily pivot levels (default: enabled) Show Weekly CPR: Toggle weekly pivot levels (default: enabled) CPR Width Threshold: Defines narrow vs wide CPR (default: 0.5% / 1.5%) Smart Money Concepts: Show FVG: Display Fair Value Gap boxes (default: enabled) Show Order Blocks: Display Order Block boxes (default: enabled) Show Breaker Blocks: Display Breaker Block labels (default: enabled) Show Liquidity Sweeps: Display liquidity sweep markers (default: enabled) FVG Min Size: Minimum gap size to display (default: 0.3%) Lookback Bars: Bars to scan for liquidity levels (default: 20) Divergence Detection: Show Divergences: Toggle divergence labels (default: enabled) RSI Length: Period for RSI calculation (default: 14) Pivot Lookback: Bars for pivot detection (default: 5) Volume Analysis: Show Volume Analysis: Toggle volume indicators (default: enabled) Volume MA Length: Period for volume moving average (default: 20) High Volume Multiplier: Threshold for high volume (default: 1.5x) Climax Volume Multiplier: Threshold for climax volume (default: 3.0x) Display Options: Show Dashboard: Toggle confluence score table (default: enabled) Max FVG Boxes: Limit displayed FVG boxes (default: 20) Max OB Boxes: Limit displayed Order Block boxes (default: 15) Label Spacing: Minimum bars between labels to prevent overlap (default: 10-15) How to Use This Indicator Step 1: Identify Market Structure Check CPR position and width. Narrow CPR suggests breakout potential, wide CPR suggests range-bound conditions. Step 2: Look for SMC Confluence Identify FVGs, Order Blocks, and recent liquidity sweeps. These zones often provide high-probability entry areas. Step 3: Check for Divergences Look for divergence labels at swing points. Multiple oscillator divergences increase signal strength. Step 4: Confirm with Volume Ensure volume supports the move. Rising delta + high volume confirms bullish moves, falling delta + high volume confirms bearish moves. Step 5: Review Confluence Score Check the dashboard. Scores above 70 indicate strong confluence. Individual component scores show which factors are contributing. Step 6: Wait for Price Action Confirmation The indicator identifies zones and conditions, but wait for price action confirmation (candlestick patterns, breakouts, etc.) before entering trades. Best Practices Use on 15-minute to 4-hour timeframes for optimal signal quality Combine with proper risk management - indicator shows zones, not exact entries Pay attention to confluence score - higher scores generally indicate better setups Watch for FVG fills and Order Block retests as entry triggers Liquidity sweeps followed by reversal often provide excellent risk:reward entries Divergences work best when combined with SMC zones or CPR levels Volume confirmation is critical - avoid low-volume signals Indicator Limitations Does not provide exact entry/exit signals - requires trader interpretation Can generate false signals in choppy, low-volume conditions Multiple visual elements may clutter chart - adjust display settings as needed Divergences can persist longer than expected - price can continue trending despite divergence FVGs and Order Blocks don't always get retested - not every zone provides entry opportunity Confluence score is a guide, not a guarantee - high scores can still result in losing trades Requires understanding of SMC concepts and CPR analysis for effective use Performance varies across different markets and timeframes Technical Implementation Built with Pine Script v6 using: Custom CPR calculations with width analysis Box and label management with anti-overlap logic Persistent variables for tracking Order Blocks and Breaker Blocks Pivot-based divergence detection across multiple oscillators Volume delta calculation with cumulative tracking Real-time confluence scoring system Dynamic dashboard with component breakdown The code is fully open-source and can be modified to suit individual trading styles and preferences. Originality Statement This indicator is original in its integration approach. While individual components (CPR, FVG, Order Blocks, RSI divergence, volume analysis) are established concepts, this mashup is justified because: It synthesizes five distinct methodologies that address different market aspects The confluence scoring system provides quantitative measurement of setup quality Anti-overlap logic and timeframe-adaptive filtering reduce visual clutter Component integration creates layered analysis not available in individual indicators The combination helps identify zones where multiple institutional and technical factors align Each component contributes unique information: CPR provides static structure, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity analysis identifies stop hunts, and volume confirms genuine moves. The mashup's value lies in presenting these complementary perspectives simultaneously with a unified scoring system. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Technical indicators are tools for analysis, not crystal balls. Past performance and backtested results do not guarantee future performance. Market conditions change, and strategies that worked historically may not work in the future. The confluence score is a mathematical calculation based on current market data, not a prediction of future price movement. High confluence scores do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades
Индикатор Pine Script®
от officialjackofalltrades
Enigma: The ICT IFVG Engine [Dean]Enigma: The ICT IFVG Engine Enigma is a next-generation algorithmic trading system designed for price action traders utilizing Inner Circle Trader (ICT) concepts. At its core, it focuses on Inversion Fair Value Gaps (IFVG), transforming them from simple visual zones into a quantified, high-probability signal engine. Unlike standard FVG indicators, Enigma uses a proprietary Weighted Confluence Score (WCS) to filter out noise, identifying only the most significant institutional displacement events. 💎 Key Features 1. The WCS Algorithm (Weighted Confluence Score) Every potential inversion setup is scored based on a multi-factor model. A signal is only generated if the confluence exceeds a strict threshold. Factors include: Volume & Displacement: Analyzes the strength of the candle breaking the gap. Freshness: Prioritizes immediate reactions over stale zones. Context: Checks for alignment with Higher Timeframe (HTF) direction. Market Structure: Aligns signals with Fractal Highs/Lows and Break of Structure (BOS). Killzones: Boosts scores during London, NY Open, and NY PM sessions. 2. Multi-Timeframe (MTF) Context HTF FVG Overlay: Automatically projects H1, H4, and Daily FVGs onto your lower timeframe chart. Liquidity Sweeps: Identifies major liquidity runs on H1/H4/D1 to predict reversals. Trend Filters: Integrated EMA 200 and Premium/Discount arrays to ensure trade alignment. 3. Signal Classifications Enigma categorizes signals to help you understand the narrative: 🚀 PRIME: The highest probability setups (WCS > Threshold × Multiplier). 💎 SB-REV: Silver Bullet Reversals (Specific 10 AM - 11 AM NY session setups). 🚀 V-SHAPE: High-momentum "V-Reversals" characterized by immediate engulfing candles. 🌊 CONTINUATION: Trend-following entries aligned with HTF flow. ♻️ REVERSAL: Counter-trend entries triggered after a confirmed liquidity sweep. 4. The Quantum Matrix (Dashboard) A sophisticated on-screen dashboard that displays: Real-time signals across multiple timeframes (S30 to H1). Ghost Strategy Performance: A built-in backtesting engine that tracks the win rate of recent signals (1:1 Scalp vs. Runner mode). Current Market Bias & Session Status. 5. Visual Aids Fractal Structure: Auto-labels BOS and CHoCH. BE Lines: Automatically draws "Breakeven" levels based on recent swing points. Smart Coloring: Dynamically colors candles based on signal state or trend. 🛠️ How to Use Timeframes: Optimized for M1, M5, and M15 scalping and intraday trading. The Signal: Wait for a "PRIME" or standard signal label (Long/Short). Long: Price aggressively breaks above a Bearish FVG (turning it into a Bullish IFVG). Short: Price aggressively breaks below a Bullish FVG. Confirmation: Look at the Quantum Matrix. Are higher timeframes aligning? Is the "Bias" text colored in your direction? Entry & Stop: Enter on the close of the signal candle or a retest of the box. Stop Loss: Placed at the recent Swing High/Low (marked by the Fractal dots). Targets: Target the opposing liquidity (Fractal Highs/Lows) or the auto-generated Target Zones. Settings Overview Aesthetics: Fully customizable colors for Neon/Dark modes. Algorithm V3: Adjust Sensitivity (Strict/Normal) and WCS Threshold to filter signal frequency. Weight Tuning: Advanced users can adjust how much weight is given to HTF Trend vs. Local Structure. Dashboard: Toggle the Quantum Matrix or Performance stats on/off. Disclaimer: This indicator is a tool for market analysis and does not constitute financial advice. Past performance shown in the Ghost Matrix is not indicative of future results.
Индикатор Pine Script®
от dean0815
SPX Specter v5.1 - Institutional Confluence EngineBuilt for intraday traders who want clean, actionable signals without the noise. Specter combines VWAP structure, multi-timeframe trend analysis, and quality-gated signals into one overlay — no separate panes, no clutter. What it does: Specter watches for two high-probability setups during the morning session when SPY has the most edge, and marks exact entries with stop-loss and take-profit levels drawn on chart. Signals: - Breakout (ORB) — First clean break of the 15-minute opening range. One entry per day, no whipsaws. Requires volume confirmation. - Pullback (PB) — Trend pullback to EMA 20 or VWAP with breakout confirmation. Uses a Setup → Arm → Confirm chain so you only enter after the bounce is validated. Every signal must pass binary quality gates before firing: - ADX trend strength - EMA 20/50 spacing (no bunched-EMA fakes) - Relative volume (institutional participation) - VWAP alignment (longs above, shorts below) - Multi-timeframe trend (15m + 1H + 4H weighted) - VIX filter (suppresses signals when VIX > 30) Key Levels on Chart: - VWAP with ±1σ and ±2σ bands - EMA 20 / 50 (200 optional) - 15-minute Opening Range box - Overnight (Globex) High / Low - Previous Day High / Low / Close - Globex Trap labels (sweep + reverse at overnight levels) Dashboard: Compact panel showing session window, market regime (Uptrend / Choppy / Wild), trend strength, volume, higher-timeframe bias, VIX status, nearest key level, and active signal — all in plain English. Anti-Overtrade: - Max signals per day cap - Cooldown between signals - Pullback setups expire after 20 minutes - Breakout locks after first entry Built for: SPY, SPX, ES, MES on 2-minute to 15-minute charts. Parameters are pre-tuned from one year of backtesting on SPY 2m. Works best: Morning session (9:30 AM – 12:00 PM ET) where intraday edge is strongest.
Индикатор Pine Script®
от blazethatish
Titan Investments|Quantitative THEMIS|Pro|BINANCE:BTCUSDTP:4hInvestment Strategy (Quantitative Trading) | 🛑 | Watch "LIVE" and 'COPY' this strategy in real time:           🔗 Link: www.tradingview.com Hello, welcome, feel free 🌹💐 Since the stone age to the most technological age, one thing has not changed, that which continues impress human beings the most, is the other human being! Deep down, it's all very simple or very complicated, depends on how you look at it. I believe that everyone was born to do something very well in life. But few are those who have, let's use the word 'luck' . Few are those who have the 'luck' to discover this thing. That is why few are happy and successful in their jobs and professions. Thank God I had this 'luck' , and discovered what I was born to do well. And I was born to program. 👨‍💻 📋 Summary : Project Titan 0️⃣     : 🦄 Project Titan 1️⃣     : ⚖️ Quantitative THEMIS 2️⃣     : 🏛️ Titan Community 3️⃣     : 👨‍💻 Who am I ❔ 4️⃣     : ❓ What is Statistical/Probabilistic Trading ❓ 5️⃣     : ❓ How Statistical/Probabilistic Trading works ❓ 6️⃣     : ❓ Why use a Statistical/Probabilistic system ❓ 7️⃣     : ❓ Why the human brain is not prepared to do Trading ❓ 8️⃣     : ❓ What is Backtest ❓ 9️⃣     : ❓ How to build a Consistent system ❓ 🔟     : ❓ What is a Quantitative Trading system ❓ 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ 1️⃣4️⃣ : 🔧 Fixed Technical 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) 1️⃣6️⃣ : ⚠️ Risk Profile 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) 1️⃣8️⃣ : 💸 Initial Capital 1️⃣9️⃣ : ⚙️ Entry Options 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' 2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Pro|BINANCE:BTCUSDTP:4h 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 3️⃣0️⃣ : 🛠️ Roadmap 3️⃣1️⃣ : 🧻 Notes ❕ 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 3️⃣3️⃣ : ♻️ ® No Repaint 3️⃣4️⃣ : 🔒 Copyright ©️ 3️⃣5️⃣ : 👏 Acknowledgments 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 0️⃣ : 🦄 Project Titan This is the first real, 100% automated Quantitative Strategy made available to the public and the pinescript community for TradingView. You will be able to automate all signals of this strategy for your broker , centralized or decentralized and also for messaging services : Discord, Telegram or Twitter . This is the first strategy of a larger project, in 2023, I will provide a total of 6 100% automated 'Quantitative' strategies to the pinescript community for TradingView. The future strategies to be shared here will also be unique , never before seen, real 'Quantitative' bots with real, validated results in real operation. Just like the 'Quantitative THEMIS' strategy, it will be something out of the loop throughout the pinescript/tradingview community, truly unique tools for building mutual wealth consistently and continuously for our community. 1️⃣ : ⚖️ Quantitative THEMIS : Titan Investments|Quantitative THEMIS|Pro|BINANCE:BTCUSDTP:4h This is a truly unique and out of the curve strategy for BTC /USD . A truly real strategy, with real, validated results and in real operation. A unique tool for building mutual wealth, consistently and continuously for the members of the Titan community. Initially we will operate on a monthly, quarterly, annual or biennial subscription service. Our goal here is to build a great community, in exchange for an extremely fair value for the use of our truly unique tools, which bring and will bring real results to our community members. With this business model it will be possible to provide all Titan users and community members with the purest and highest degree of sophistication in the market with pinescript for tradingview, providing unique and truly profitable strategies. My goal here is to offer the best to our members! The best 'pinescript' tradingview service in the world! We are the only Start-Up in the world that will decentralize real and full access to truly real 'quantitative' tools that bring and will bring real results for mutual and ongoing wealth building for our community. 2️⃣ : 🏛️ Titan Community : 👽 Pro 🔁 Aff 🛸 Become a Titan Pro 👽 To get access to the strategy: "Quantitative THEMIS" , and future Titan strategies in a 100% automated way, along with all tutorials for automation. Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. 👽 Pro 🅼 Monthly 👽 Pro 🆀 Quarterly 👽 Pro🅰 Annual 👽 Pro👾Two Years You will have access to a truly unique system that is out of the curve . A 100% real, 100% automated, tested, validated, profitable, and in real operation strategy. Become a Titan Affiliate 🛸 By becoming a Titan Affiliate 🛸, you will automatically receive 50% of the value of each new subscription you refer . You will receive 50% for any of the above plans that you refer . This way we will encourage our community to grow in a fair and healthy way, because we know what we have in our hands and what we deliver real value to our users. We are at the highest level of sophistication in the market, the consistency here and the results here speak for themselves. So growing our community means growing mutual wealth and raising collective conscience. Wealth must be created not divided. And here we are creating mutual wealth on all ends and in all ways. A non-zero sum system, where everybody wins. 3️⃣ : 👨‍💻 Who am I ❔ My name is FilipeSoh I am 26 years old, Technical Analyst, Trader, Computer Engineer, pinescript Specialist, with extensive experience in several languages and technologies. For the last 4 years I have been focusing on developing, editing and creating pinescript indicators and strategies for Tradingview for people and myself. Full-time passionate workaholic pinescript developer with over 10,000 hours of pinescript development. • Pinescript expert ▬Tradingview. • Specialist in Automated Trading • Specialist in Quantitative Trading. • Statistical/Probabilistic Trading Specialist - Mark Douglas Scholl. • Inventor of the 'Classic Forecast' Indicators. • Inventor of the 'Backtest Table'. 4️⃣ : ❓ What is Statistical/Probabilistic Trading ❓ Statistical/probabilistic trading is the only way to get a positive mathematical expectation regarding the market and consequently that is the only way to make money consistently from it. I will present below some more details about the Quantitative THEMIS strategy, it is a real strategy, tested, validated and in real operation, 'Skin in the Game' , a consistent way to make money with statistical/probabilistic trading in a 100% automated. I am a Technical Analyst , I used to be a Discretionary Trader , today I am 100% a Statistical Trader . I've gotten rich and made a lot of money, and I've also lost a lot with 'leverage'. That was a few years ago. The book that changed everything for me was "Trading in The Zone" by Mark Douglas. That's when I understood that the market is just a game of statistics and probability, like a casino! It was then that I understood that the human brain is not prepared for trading, because it involves triggers and mental emotions. And emotions in trading and in making trading decisions do not go well together, not in the long run, because you always have the burden of being wrong with the outcome of that particular position. But remembering that the market is just a statistical game! 5️⃣ : ❓ How Statistical/Probabilistic Trading works ❓ Let's use a 'coin' as an example: If we toss a 'coin' up 10 times. Do you agree that it is impossible for us to know exactly the result of the 'plays' before they actually happen? As in the example above, would you agree, that we cannot "guess" the outcome of a position before it actually happens? As much as we cannot "guess" whether the coin will drop heads or tails on each flip. We can analyze the "backtest" of the 10 moves made with that coin: If we analyze the 10 moves and count the number of times the coin fell heads or tails in a specific sequence, we then have a percentage of times the coin fell heads or tails, so we have a 'backtest' of those moves. Then on the next flip we can now assume a point or a favorable position for one side, the side with the highest probability . In a nutshell, this is more or less how probabilistic statistical trading works. As Statistical Traders we can never say whether such a Trader/Position we take will be a winner or a loser. But still we can have a positive and consistent result in a "sequence" of trades, because before we even open a position, backtests have already been performed so we identify an anomaly and build a system that will have a positive statistical advantage in our favor over the market. The advantage will not be in one trade itself, but in the "sequence" of trades as a whole! Because our system will work like a casino, having a positive mathematical expectation relative to the players/market. Design, develop, test models and systems that can take advantage of market anomalies, until they change. Be the casino! - Mark Douglas 6️⃣ : ❓ Why use a Statistical/Probabilistic system ❓ In recent years I have focused and specialized in developing 100% automated trading systems, essentially for the cryptocurrency market. I have developed many extremely robust and efficient systems, with positive mathematical expectation towards the market. These are not complex systems per se , because here we want to avoid 'over-optimization' as much as possible. As Da Vinci said: "Simplicity is the highest degree of sophistication". I say this because I have tested, tried and developed hundreds of systems/strategies. I believe I have programmed more than 10,000 unique indicators/strategies, because this is my passion and purpose in life. I am passionate about what I do, completely! I love statistical trading because it is the only way to get consistency in the long run! This is why I have studied, applied, developed, and specialized in 100% automated cryptocurrency trading systems. The reason why our systems are extremely "simple" is because, as I mentioned before, in statistical trading we want to exploit the market anomaly to the maximum, that is, this anomaly will change from time to time, usually we can exploit a trading system efficiently for about 6 to 12 months, or for a few years, that is; for fixed 'scalpers' systems. Because at some point these anomalies will be identified , and from the moment they are identified they will be exploited and will stop being anomalies . With the system presented here; you can even copy the indicators and input values shared here; However; what I have to offer you is: it is me , our team , and our community ! That is, we will constantly monitor this system, for life , because our goal here is to create a unique , perpetual , profitable , and consistent system for our community. Myself , our team and our community will keep this script periodically updated , to ensure the positive mathematical expectation of it. So we don't mind sharing the current parameters and values , because the real value is also in the future updates that this system will receive from me and our team , guided by our culture and our community of real users ! As we are hosted on 'tradingview', all future updates for this strategy, will be implemented and updated automatically on your tradingview account. What we want here is: to make sure you get gains from our system, because if you get gains , our ecosystem will grow as a whole in a healthy and scalable way, so we will be generating continuous mutual wealth and raising the collective consciousness . People Need People: 3️⃣🅿 7️⃣ : ❓ Why the human brain is not prepared to do Trading ❓ Today my greatest skill is to develop statistically profitable and 100% automated strategies for 'pinescript' tradingview. Note that I said: 'profitable' because in fact statistical trading is the only way to make money in a 'consistent' way from the market. And consequently have a positive wealth curve every cycle, because we will be based on mathematics, not on feelings and news. Because the human brain is not prepared to do trading. Because trading is connected to the decision making of the cerebral cortex. And the decision making is automatically linked to emotions, and emotions don't match with trading decision making, because in those moments, we can feel the best and also the worst sensations and emotions, and this certainly affects us and makes us commit grotesque mistakes! That's why the human brain is not prepared to do trading. If you want to participate in a fully automated, profitable and consistent trading system; be a Titan Pro 👽 I believe we are walking an extremely enriching path here, not only in terms of financial returns for our community, but also in terms of knowledge about probabilistic and automated statistical trading. You will have access to an extremely robust system, which was built upon very strong concepts and foundations, and upon the world's main asset in a few years: Bitcoin . We are the tip of the best that exists in the cryptocurrency market when it comes to probabilistic and automated statistical trading. Result is result! Me being dressed or naked. This is just the beginning! But there is a way to consistently make money from the market. Being the Casino! - Mark Douglas 8️⃣ : ❓ What is Backtest ❓ Imagine the market as a purely random system, but even in 'randomness' there are patterns. So now imagine the market and statistical trading as follows: Repeating the above 'coin' example, let's think of it as follows: If we toss a coin up 10 times again. It is impossible to know which flips will have heads or tails, correct? But if we analyze these 10 tosses, then we will have a mathematical statistic of the past result, for example, 70 % of the tosses fell 'heads'. That is: 7 moves fell on "heads" . 3 moves fell on "tails" . So based on these conditions and on the generic backtest presented here, we could adopt " heads " as our system of moves, to have a statistical and probabilistic advantage in relation to the next move to be performed. That is, if you define a system, based on backtests , that has a robust positive mathematical expectation in relation to the market you will have a profitable system. For every move you make you will have a positive statistical advantage in your favor over the market before you even make the move. Like a casino in relation to all its players! The casino does not have an advantage over one specific player, but over all players, because it has a positive mathematical expectation about all the moves that night. The casino will always have a positive statistical advantage over its players. Note that there will always be real players who will make real, million-dollar bankrolls that night, but this condition is already built into the casino's 'strategy', which has a pre-determined positive statistical advantage of that night as a whole. Statistical trading is the same thing, as long as you don't understand this you will keep losing money and consistently. 9️⃣ : ❓ How to build a Consistent system ❓ See most traders around the world perform trades believing that that specific position taken will make them filthy rich, because they simply believe faithfully that the position taken will be an undoubted winner, based on a trader's methodology: 'trading a trade' without analyzing the whole context, just using 'empirical' aspects in their system. But if you think of trading, as a sequence of moves. You see, 'a sequence' ! When we think statistically, it doesn't matter your result for this , or for the next specific trade , but the final sequence of trades as a whole. As the market has a random system of results distribution , if your system has a positive statistical advantage in relation to the market, at the end of that sequence you'll have the biggest probability of having a winning bank. That's how you do real trading! And with consistency! Trading is a long term game, but when you change the key you realize that it is a simple game to make money in a consistent way from the market, all you need is patience. Even more when we are based on Bitcoin, which has its 'Halving' effect where, in theory, we will never lose money in 3 to 4 years intervals, due to its scarcity and the fact that Bitcoin is the 'discovery of digital scarcity' which makes it the digital gold, we believe in this thesis and we follow Satoshi's legacy. So align Bitcoin with a probabilistic statistical trading system with a positive mathematical expectation of the market and 100% automated with the long term, and all you need is patience, and you will become rich. In fact Bitcoin by itself is already a path, buy, wait for each halving and your wealth will be maintained. No inflation, unlike fiat currencies. This is a complete and extremely robust strategy, with the most current possible and 'not possible' techniques involved and applied here. Today I am at another level in developing 100% automated 'quantitative' strategies. I was born for this! 🔟 : ❓ What is a Quantitative Trading system ❓ In addition to having access to a revolutionary strategy you will have access to disruptive 100% multifunctional tables with the ability to perform 'backtests' for better tracking and monitoring of your system on a customized basis. I would like to emphasize one thing, and that is that you keep this in mind. Today my greatest skill in 'pinescript' is to build indicators, but mainly strategies, based on statistical and probabilistic trading, with a postive mathematical expectation in relation to the market, in a 100% automated way. This with the goal of building a consistent and continuous positive equity curve through mathematics using data, converting it into statistical / probabilistic parameters and applying them to a Quantitative model. Before becoming a Quantitative Trader , I was a Technical Analyst and a Discretionary Trader . First as a position trader and then as a day trader. Before becoming a Trader, I trained myself as a Technical Analyst , to masterly understand the shape and workings of the market in theory. But everything changed when I met 'Mark Douglas' , when I got to know his works, that's when my head exploded 🤯, and I started to understand the market for good! The market is nothing more than a 'random' system of distributing results. See that I said: 'random' . Do yourself a mental exercise. Is there really such a thing as random ? I believe not, as far as we know maybe the 'singularity'. So thinking this way, to translate, the market is nothing more than a game of probability, statistics and pure mathematics. Like a casino! What happens is that most traders, whenever they take a position, take it with all the empirical certainty that such position will win or lose, and do not take into consideration the total sequence of results to understand their place in the market. Understanding your place in the market gives you the ability to create and design systems that can exploit the present market anomaly, and thus make money statistically, consistently, and 100% automated. Thinking of it this way, it is easy to make money from the market. There are many ways to make money from the market, but the only consistent way I know of is through 'probabilistic and automated statistical trading'. 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ There are some fundamental points that must be addressed here in order to understand what makes up a system based on statistics and probability applied to a quantitative model. When we talk about 'discretionary' trading, it is a trading system based on human decisions after the defined 'empirical' conditions are met. It is quite another thing to build a fully automated system without any human interference/interaction . That said: Building a statistically profitable system is perfectly possible, but this is a high level task , but with possible high rewards and consistent gains. Here you will find a real "Skin In The Game" strategy. With all due respect, but the vast majority of traders who post strategies on TradingView do not understand what they are doing. Most of them do not understand the minimum complexity involved in the main variable for the construction of a real strategy, the mother variable: "strategy". I say this by my own experience, because I have analyzed practically all the existing publications of TradingView + 200,000 indicators and strategies. I breathe pinescript, I eat pinescript, I sleep pinescript, I bathe pinescript, I live TradingView. But the main advantage for the TradingView users, is that all entry and exit orders made by this strategy can be checked and analyzed thoroughly, to validate and prove the veracity of this strategy, because this is a 100% real strategy. Here there is a huge world of possibilities, but only one way to build a 'pinescript strategy' that will work correctly aligned to the real world with real results . There are some fundamental points to take into consideration when building a profitable trading system: The most important of these for me is: 'DrawDown' . Followed by: 'Hit Rate' . And only after that we use the parameter: 'Profit'. See, this is because here, we are dealing with the 'imponderable' , and anything can happen in this scenario. But there is one thing that makes us sleep peacefully at night, and that is: controlling losses . That is, in other words: controlling the DrawDown . The amateur is concerned with 'winning', the professional is concerned with conserving capital. If we have the losses under control, then we can move on to the other two parameters: hit rate and profit. See, the second most important factor in building a system is the hit rate. I say this from my own experience. I have worked with many systems with a 'low hit rate', but extremely profitable. For example: systems with hit rates of 40 to 50%. But as much as statistically and mathematically the profit is rewarding, operating systems with a low hit rate is always very stressful psychologically. That's why there are two big reasons why when I build an automated trading system, I focus on the high hit rate of the system, they are 1 - To reduce psychological damage as much as possible . 2 - And more important , when we create a system with a 'high hit rate' , there is a huge intrinsic advantage here, that most statistic traders don't take in consideration. That is: knowing more quickly when the system stops being functional. The main advantage of a system with a high hit rate is: to identify when the system stops being functional and stop exploiting the market's anomaly. Look: When we are talking about trading and random distribution of results on the market, do you agree that when we create a trading system, we are focused on exploring some anomaly of that market? When that anomaly is verified by the market, it will stop being functional with time. That's why trading systems, 'scalpers', especially for cryptocurrencies, need constant monitoring, quarterly, semi-annually or annually. Because market movements change from time to time. Because we go through different cycles from time to time, such as congestion cycles, accumulation , distribution , volatility , uptrends and downtrends . 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ You see there is a very important point that must be stressed here. As we are always trying to exploit an 'anomaly' in the market. So the 'number' of indicators/tools that will integrate the system is of paramount importance. But most traders do not take this into consideration. To build a professional, robust, consistent, and profitable system, you don't need to use hundreds of indicators to build your setup. This will actually make it harder to read when the setup stops working and needs some adjustment. So focusing on a high hit rate is very important here, this is a fundamental principle that is widely ignored , and with a high hit rate, we can know much more accurately when the system is no longer functional much faster. As Darwin said: "It is not the strongest or the most intelligent that wins the game of life, it is the most adapted. So simple systems, as contradictory as it may seem, are more efficient, because they help to identify inflection points in the market much more quickly. 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ See I have built, hundreds of thousands of indicators and 'pinescript' strategies, hundreds of thousands. This is an extremely professional, robust and profitable system. Based on the currency pairs: BTC /USDT There are many ways and avenues to build a profitable trading setup/system. And actually this is not a difficult task, taking in consideration, as the main factor here, that our trading and investment plan is for the long term, so consequently we will face scenarios with less noise. He who is in a hurry eats raw. As mentioned before. Defining trends in pinescript is technically a simple task, the hardest task is to determine congestion zones with low volume and volatility, it's in these moments that many false signals are generated, and consequently is where most setups face their maximum DrawDown. That's why this strategy was strictly and thoroughly planned, built on a very solid foundation, to avoid as much noise as possible, for a positive and consistent equity curve in each market cycle, 'Consistency' is our 'Mantra' around here. 1️⃣4️⃣ : 🔧 Fixed Technical • Strategy:      Titan Investments|Quantitative THEMIS|Pro|BINANCE:BTCUSDTP:4h • Pair:             BTC/USDTP • Time Frame: 4 hours • Broker:         Binance (Recommended) For a more conservative scenario, we have built the Quantitative THEMIS for the 4h time frame, with the main focus on consistency. So we can avoid noise as much as possible! 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) In order to build a 'perpetual' system specific to BTC/USDT, it took a lot of testing, and more testing, and a lot of investment and research. There is one initial and fundamental point that we can address to justify the incredible consistency presented here. That fundamental point is our exit via Take Profit or Stop Loss percentage (%). 🎯 Take Profit (%) 🛑 Stop Loss (%) See, today I have been testing some more advanced backtesting models for some cryptocurrency systems. In which I perform 'backtest of backtest', i.e. we use a set of strategies each focused on a principle, operating individually, but they are part of something unique, i.e. we do 'backtests' of 'backtests' together. What I mean is that we do a lot of backtesting around here. I can assure you, that always the best output for a trading system is to set fixed output values! In other words: 🎯 Take Profit (%) 🛑 Stop Loss (%) This happens because statistically setting fixed exit structures in the vast majority of times, presents a superior result on the capital/equity curve, throughout history and for the vast majority of setups compared to other exit methods. This is due to a mathematical principle of simplicity, 'avoiding more noise'. Thus whenever the Quantitative THEMIS strategy takes a position it has a target and a defined maximum stop percentage. 1️⃣6️⃣ : ⚠️ Risk Profile The strategy, currently has 3 risk profiles ⚠️ patterns for 'fixed percentage exits': Take Profit (%) and Stop Loss (%) . They are: ⚠️ Rich's Profiles ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 % ❌Ⓜ️ Moderate:     🎯 TP=2.8 % 🛑 SL=2.7 % ❌🅰 Aggressive:    🎯 TP=1.6 % 🛑 SL=6.9 % You will be able to select and switch between the above options and profiles through the 'input' menu of the strategy by navigating to the "⚠️ Risk Profile" menu. You can then select, test and apply the Risk Profile above that best suits your risk management, expectations and reality , as well as customize all the 'fixed exit' values through the TP and SL menus below. 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) The strategy currently also has 'Moving Exits' based on indicator signals. These are Moving Exits (Indicators) 📈 LONG : (EXIT) 🧃 (MAO) Short : true 📉 SHORT : (EXIT) 🧃 (MAO) Long: false You can select and toggle between the above options through the 'input' menu of the strategy by navigating to the "LONG : Exit" and "SHORT : Exit" menu. 1️⃣8️⃣ : 💸 Initial Capital By default the "Initial Capital" set for entries and backtests of this strategy is: 10000 $ You can set another value for the 'Starting Capital' through the tradingview menu under "properties" , and edit the value of the "Initial Capital" field. This way you can set and test other 'Entry Values' for your trades, tests and backtests. 1️⃣9️⃣ : ⚙️ Entry Options By default the 'order size' set for this strategy is 100 % of the 'initial capital' on each new trade. You can set and test other entry options like : contracts , cash , % of equity You should make these changes directly in the input menu of the strategy by navigating to the menu "⚙️ Properties : TradingView" below. ⚙️ Properties : (TradingView) 📊 Strategy Type:   strategy.position_size != 1 📝💲 % Order Type: % of equity 📝💲 % Order Size: 100 Leverage:             1 So you can define and test other 'Entry Options' for your trades, tests and backtests. 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' It is possible to automate the signals of this strategy for any centralized or decentralized broker, as well as for messaging services: Discord, Telegram and Twitter. All in an extremely simple and uncomplicated way through the tutorials available in PDF /VIDEO for our Titan Pro 👽 subscriber community. With our tutorials in PDF and Video it will be possible to automate the signals of this strategy for the chosen service in an extremely simple way with less than 10 steps only. Tradingview naturally doesn't count with native integration between brokers and tradingview. But it is possible to use 'third party services' to do the integration and automation between Tradingview and your centralized or decentralized broker. Here are the standard, available and recommended 'third party services' to automate the signals from the 'Quantitative THEMIS' strategy on the tradingview for your broker: 1) Wundertrading (Recommended): 2) 3commas:                                3) Zignaly:                                   4) Aleeert.com    (Recommended): 5) Alertatron:                               Note! 'Third party services' cannot perform 'withdrawals' via their key 'API', they can only open positions, so your funds will always be 'safe' in your brokerage firm, being traded via the 'API', when they receive an entry and exit signal from this strategy. 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges You can automate this strategy for any of the brokers below, through your broker's 'API' by connecting it to the 'third party automation services' for tradingview available and mentioned in the menu above: 1) Binance (Recommended) 2) Bitmex 3) Bybit 4) KuCoin 5) Deribit 6) OKX 7) Coinbase 8) Huobi 9) Bitfinex 10) Bitget 11) Bittrex 12) Bitstamp 13) Gate. io 14) Kraken 15) Gemini 16) Ascendex 17) VCCE 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' You can also automate and monitor the signals of this strategy much more efficiently by sending them to the following popular messaging services: 1) Discord 2) Telegram 3) Twitter 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' It will also be possible to copy/replicate the entries and exits of this strategy to your broker in an extremely simple and agile way, through the available copy-trader services. This way it will be possible to replicate the signals of this strategy at each entry and exit to your broker through the API connecting it to the integrated copy-trader services available through the tradingview automation services below: 1) Wundetrading: 2) Zignaly:           2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ I believe that today I am at another level in 'pinescript' development. I consider myself today a true unicorn as a pinescript developer, someone unique and very rare. If you choose another tool or another pinescript service, this tool will be just another one, with no real results. But if you join our Titan community, you will have access to a unique tool! And you will get real results! I already earn money consistently with statistical and automated trading and as an expert pinescript developer. I am here to evolve my skills as much as possible, and one day become a pinescript 'Wizard'. So excellence, quality and professionalism will always be my north here. You will never find a developer like me, and who will take so seriously such a revolutionary project as this one. A Maverick! ▬ The man never stops! Here you will find the highest degree of sophistication and development in the market for 'pinescript'. You will get the best of me and the best of pinescript possible. Let me show you how a professional in my field does it. Become a Titan Pro Member 👽 and get Full Access to this strategy and all the Automation Tutorials. Be the Titan in your life! 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ Get financial return for your referrals, Decentralize the World, and raise the collective consciousness. 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Pro|BINANCE:BTCUSDTP:4h ® Titan Investimentos | Quantitative THEMIS ⚖️ | Pro 👽 2.6 | Dev: © FilipeSoh 🧙 | 🤖 100% Automated : Discord, Telegram, Twitter, Wundertrading, 3commas, Zignaly, Aleeert, Alertatron, Uniswap-v3 | BINANCE:BTCUSDTPERP 4h 🛒 Subscribe this strategy  ❗️  Be a Titan Member 🏛️ 🛒 Titan Pro        👽   🏛️ Titan Pro        👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) 🛒 Titan Affiliate 🛸  🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission 📋 Summary : QT THEMIS ⚖️ 🕵️‍♂️ Check This Strategy..................................................................0 🦄 ® Titan Investimentos...............................................................1 👨‍💻 © Developer..........................................................................2 📚 Signal Automation Tutorials : (PDF/VIDEO).......................................3 👨‍🔧 Revision...............................................................................4 📊 Table : (BACKTEST)..................................................................5 📊 Table : (INFORMATIONS).............................................................6 ⚙️ Properties : (TRADINGVIEW)........................................................7 📆 Backtest : (TRADINGVIEW)..........................................................8 ⚠️ Risk Profile...........................................................................9 🟢 On 🔴 Off : (LONG/SHORT).......................................................10 📈 LONG : (ENTRY)....................................................................11 📉 SHORT : (ENTRY)...................................................................12 📈 LONG : (EXIT).......................................................................13 📉 SHORT : (EXIT)......................................................................14 🧩 (EI) External Indicator.............................................................15 📡 (QT) Quantitative...................................................................16 🎠 (FF) Forecast......................................................................17 🅱 (BB) Bollinger Bands................................................................18 🧃 (MAP) Moving Average Primary......................................................19 🧃 (MAP) Labels.........................................................................20 🍔 (MAQ) Moving Average Quaternary.................................................21 🍟 (MACD) Moving Average Convergence Divergence...............................22 📣 (VWAP) Volume Weighted Average Price........................................23 🪀 (HL) HILO..........................................................................24 🅾 (OBV) On Balance Volume.........................................................25 🥊 (SAR) Stop and Reverse...........................................................26 🛡️ (DSR) Dynamic Support and Resistance..........................................27 🔊 (VD) Volume Directional..........................................................28 🧰 (RSI) Relative Momentum Index.................................................29 🎯 (TP) Take Profit %..................................................................30 🛑 (SL) Stop Loss %....................................................................31 🤖 Automation Selected...............................................................32 📱💻 Discord............................................................................33 📱💻 Telegram..........................................................................34 📱💻 Twitter...........................................................................35 🤖 Wundertrading......................................................................36 🤖 3commas............................................................................37 🤖 Zignaly...............................................................................38 🤖 Aleeert...............................................................................39 🤖 Alertatron...........................................................................40 🤖 Uniswap-v3..........................................................................41 🧲🤖 Copy-Trading....................................................................42 ♻️ ® No Repaint........................................................................43 🔒 Copyright ©️..........................................................................44 🏛️ Be a Titan Member..................................................................45 Nº Active Users..........................................................................46 ⏱ Time Left............................................................................47 | 0 | 🕵️‍♂️ Check This Strategy         🕵️‍♂️ Version Demo: 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available         🕵️‍♂️ Version Pro: 👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) | 1 | 🦄 ® Titan Investimentos         Decentralizing the World 🗺         Raising the Collective Conscience 🗺                 🦄Site:                      🦄TradingView: www.tradingview.com         🦄Discord:                 🦄Telegram:              🦄Youtube:                🦄Twitter:                 🦄Instagram:             🦄TikTok:                 🦄Linkedin:               🦄E-mail:          | 2 | 👨‍💻 © Developer         🧠 Developer:    @FilipeSoh🧙         📺 TradingView: www.tradingview.com         ☑️ Linkedin:               ✅ Fiverr:                  ✅ Upwork:                🎥 YouTube:               🐤 Twitter:                🤳 Instagram:    | 3 | 📚 Signal Automation Tutorials : (PDF/VIDEO)         📚 Discord:           🔗 Link: 🔒Titan Pro👽         📚 Telegram:        🔗 Link: 🔒Titan Pro👽         📚 Twitter:           🔗 Link: 🔒Titan Pro👽         📚 Wundertrading: 🔗 Link: 🔒Titan Pro👽         📚 3comnas:         🔗 Link: 🔒Titan Pro👽         📚 Zignaly:           🔗 Link: 🔒Titan Pro👽         📚 Aleeert:           🔗 Link: 🔒Titan Pro👽         📚 Alertatron:       🔗 Link: 🔒Titan Pro👽         📚 Uniswap-v3:     🔗 Link: 🔒Titan Pro👽         📚 Copy-Trading:   🔗 Link: 🔒Titan Pro👽 | 4 | 👨‍🔧 Revision         👨‍🔧 Start Of Operations: 01 Jan 2019 21:00 -0300 💡 Start Of Operations (Skin in the game) : Revision 1.0         👨‍🔧 Previous Review:      01 Jan 2022 21:00 -0300 💡 Previous Review : Revision 2.0         👨‍🔧 Current Revision:     01 Jan 2023 21:00 -0300 💡 Current Revision : Revision 2.6         👨‍🔧 Next Revision:         28 May 2023 21:00 -0300 💡 Next Revision : Revision 2.7 | 5 | 📊 Table : (BACKTEST)         📊 Table: true         🖌️ Style:  label.style_label_left         📐 Size:   size_small         📏 Line:  defval         🎨 Color: #131722 | 6 | 📊 Table : (INFORMATIONS)         📊 Table: false         🖌️ Style:  label.style_label_right         📐 Size:   size_small         📏 Line:  defval         🎨 Color: #131722 | 7 | ⚙️ Properties : (TradingView)         📊 Strategy Type:  strategy.position_size != 1         📝💲 % Order Type: % of equity         📝💲 % Order Size: 100 %         🚀 Leverage:        1 | 8 | 📆 Backtest : (TradingView)         🗓️ Mon:     true         🗓️ Tue:      true         🗓️ Wed:     true         🗓️ Thu:      true         🗓️ Fri:       true         🗓️ Sat:       true         🗓️ Sun:      true         📆 Range:  custom         📆 Start:    UTC 31 Oct 2008 00:00         📆 End:      UTC 31 Oct 2030 23:45         📆 Session: 0000-0000         📆 UTC:     UTC | 9 | ⚠️ Risk Profile         ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 %         ❌Ⓜ️ Moderate:     🎯 TP=2.8 % 🛑 SL=2.7 %         ❌🅰 Aggressive:    🎯 TP=1.6 % 🛑 SL=6.9 % | 10 | 🟢 On 🔴 Off : (LONG/SHORT)          🟢📈 LONG:  true          🟢📉 SHORT: true | 11 | 📈 LONG : (ENTRY)          📡 (QT) Long:       true          🧃 (MAP) Long:      false          🅱 (BB) Long:       false          🍟 (MACD) Long: false          🅾 (OBV) Long:     false | 12 | 📉 SHORT : (ENTRY)          📡 (QT) Short:       true          🧃 (MAP) Short:      false          🅱 (BB) Short:       false          🍟 (MACD) Short: false          🅾 (OBV) Short:     false | 13 | 📈 LONG : (EXIT)          🧃 (MAP) Short: true | 14 | 📉 SHORT : (EXIT)          🧃 (MAP) Long: false | 15 | 🧩 (EI) External Indicator          🧩 (EI) Connect your external indicator/filter:             false          🧩 (EI) Connect your indicator here (Study mode only): close          🧩 (EI) Connect your indicator here (Study mode only): close | 16 | 📡 (QT) Quantitative          📡 (QT) Quantitative: true          📡 (QT) Market:        BINANCE:BTCUSDTPERP          📡 (QT) Dice:            openai | 17 | 🎠 (FF) Forecast          🎠 (FF) Include current unclosed current candle:  true          🎠 (FF) Forecast Type:                                    flat          🎠 (FF) Nº of candles to use in linear regression: 3 | 18 | 🅱 (BB) Bollinger Bands          🅱 (BB) Bollinger Bands: true          🅱 (BB) Type:               EMA          🅱 (BB) Period:             20          🅱 (BB) Source:            close          🅱 (BB) Multiplier:         2          🅱 (BB) Linewidth:        0          🅱 (BB) Color:              #131722 | 19 | 🧃 (MAP) Moving Average Primary          🧃 (MAP) Moving Average Primary: true          🧃 (MAP) BarColor:                      false          🧃 (MAP) Background:                  false          🧃 (MAP) Type:                           SMA          🧃 (MAP) Source:                        open          🧃 (MAP) Period:                         100          🧃 (MAP) Multiplier:                     2.0          🧃 (MAP) Linewidth:                    2          🧃 (MAP) Color P:                        #42bda8          🧃 (MAP) Color N:                       #801922 | 20 | 🧃 (MAP) Labels          🧃 (MAP) Labels:               true          🧃 (MAP) Style BUY ZONE:  shape.labelup          🧃 (MAP) Color BUY ZONE: #42bda8          🧃 (MAP) Style SELL ZONE: shape.labeldown          🧃 (MAP) Color SELL ZONE: #801922 | 21 | 🍔 (MAQ) Moving Average Quaternary          🍔 (MAQ) Moving Average Quaternary: true          🍔 (MAQ) BarColor:                          false          🍔 (MAQ) Background:                      false          🍔 (MAQ) Type:                                SMA          🍔 (MAQ) Source:                             close          🍔 (MAQ) Primary:                           14          🍔 (MAQ) Secondary:                        22          🍔 (MAQ) Tertiary:                           44          🍔 (MAQ) Quaternary:                      16          🍔 (MAQ) Linewidth:                         0          🍔 (MAQ) Color P:                            #42bda8          🍔 (MAQ) Color N:                            #801922 | 22 | 🍟 (MACD) Moving Average Convergence Divergence          🍟 (MACD) Macd Type:  EMA          🍟 (MACD) Signal Type: EMA          🍟 (MACD) Source:       close          🍟 (MACD) Fast:          12          🍟 (MACD) Slow:          26          🍟 (MACD) Smoothing:  9 | 23 | 📣 (VWAP) Volume Weighted Average Price          📣 (VWAP) Source:             close          📣 (VWAP) Period:              340          📣 (VWAP) Momentum A:     84          📣 (VWAP) Momentum B:    150          📣 (VWAP) Average Volume: 1          📣 (VWAP) Multiplier:          1          📣 (VWAP) Diviser:             2 | 24 | 🪀 (HL) HILO          🪀 (HL) Type:          SMA          🪀 (HL) Function:     Maverick🧙          🪀 (HL) Source H:    high          🪀 (HL) Source L:     low          🪀 (HL) Period:        20          🪀 (HL) Momentum: 26          🪀 (HL) Diviser:        2          🪀 (HL) Multiplier:    1 | 25 | 🅾 (OBV) On Balance Volume          🅾 (OBV) Type:        EMA          🅾 (OBV) Source:     close          🅾 (OBV) Period:     16          🅾 (OBV) Diviser:     2          🅾 (OBV) Multiplier: 1 | 26 | 🥊 (SAR) Stop and Reverse          🥊 (SAR) Source:     close          🥊 (SAR) High:        1.8          🥊 (SAR) Mid:         1.6          🥊 (SAR) Low:        1.6          🥊 (SAR) Diviser:     2          🥊 (SAR) Multiplier: 1 | 27 | 🛡️ (DSR) Dynamic Support and Resistance          🛡️ (DSR) Source D:       close          🛡️ (DSR) Source R:       high          🛡️ (DSR) Source S:       low          🛡️ (DSR) Momentum R: 0          🛡️ (DSR) Momentum S: 2          🛡️ (DSR) Diviser:          2          🛡️ (DSR) Multiplier:      1 | 28 | 🔊 (VD) Volume Directional          🔊 (VD) Type:          SMA          🔊 (VD) Period:        68          🔊 (VD) Momentum: 3.8          🔊 (VD) Diviser:       2          🔊 (VD) Multiplier:    1 | 29 | 🧰 (RSI) Relative Momentum Index          🧰 (RSI) Type UP:        EMA          🧰 (RSI) Type DOWN:   EMA          🧰 (RSI) Source:          close          🧰 (RSI) Period:           29          🧰 (RSI) Smoothing:     22          🧰 (RSI) Momentum R: 64          🧰 (RSI) Momentum S: 142          🧰 (RSI) Diviser:          2          🧰 (RSI) Multiplier:      1 | 30 | 🎯 (TP) Take Profit %          🎯 (TP) Take Profit: false          🎯 (TP) %:              2.2          🎯 (TP) Color:         #42bda8          🎯 (TP) Linewidth:  1 | 31 | 🛑 (SL) Stop Loss %          🛑 (SL) Stop Loss:  false          🛑 (SL) %:             2.7          🛑 (SL) Color:        #801922          🛑 (SL) Linewidth: 1 | 32 | 🤖 Automation : Discord | Telegram | Twitter | Wundertrading | 3commas | Zignaly | Aleeert | Alertatron | Uniswap-v3          🤖 Automation Selected : Discord | 33 | 🤖 Discord          🔗 Link Discord:            discord.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Discord ▬ Enter Long:  🔒Titan Pro👽          📱💻 Discord ▬ Exit Long:    🔒Titan Pro👽          📱💻 Discord ▬ Enter Short: 🔒Titan Pro👽          📱💻 Discord ▬ Exit Short:   🔒Titan Pro👽 | 34 | 🤖 Telegram          🔗 Link Telegram:          telegram.org          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Telegram ▬ Enter Long:  🔒Titan Pro👽          📱💻 Telegram ▬ Exit Long:    🔒Titan Pro👽          📱💻 Telegram ▬ Enter Short: 🔒Titan Pro👽          📱💻 Telegram ▬ Exit Short:   🔒Titan Pro👽 | 35 | 🤖 Twitter          🔗 Link Twitter:            twitter.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Twitter ▬ Enter Long:  🔒Titan Pro👽          📱💻 Twitter ▬ Exit Long:    🔒Titan Pro👽          📱💻 Twitter ▬ Enter Short: 🔒Titan Pro👽          📱💻 Twitter ▬ Exit Short:   🔒Titan Pro👽 | 36 | 🤖 Wundertrading : Binance | Bitmex | Bybit | KuCoin | Deribit | OKX | Coinbase | Huobi | Bitfinex | Bitget          🔗 Link Wundertrading:  wundertrading.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Wundertrading ▬ Enter Long:  🔒Titan Pro👽          📱💻 Wundertrading ▬ Exit Long:    🔒Titan Pro👽          📱💻 Wundertrading ▬ Enter Short: 🔒Titan Pro👽          📱💻 Wundertrading ▬ Exit Short:   🔒Titan Pro👽 | 37 | 🤖 3commas : Binance | Bybit | OKX | Bitfinex | Coinbase | Deribit | Bitmex | Bittrex | Bitstamp | Gate.io | Kraken | Gemini | Huobi | KuCoin          🔗 Link 3commas:          3commas.io          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 3commas ▬ Enter Long:  🔒Titan Pro👽          📱💻 3commas ▬ Exit Long:    🔒Titan Pro👽          📱💻 3commas ▬ Enter Short: 🔒Titan Pro👽          📱💻 3commas ▬ Exit Short:   🔒Titan Pro👽 | 38 | 🤖 Zignaly : Binance | Ascendex | Bitmex | Kucoin | VCCE          🔗 Link Zignaly:             zignaly.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          🤖 Type Automation:        Profit Sharing          🤖 Type Provider:             Webook          🔑 Key:                         🔒Titan Pro👽          🤖 pair:                         BTCUSDTP          🤖 exchange:                  binance          🤖 exchangeAccountType: futures          🤖 orderType:                 market          🚀 leverage:                   1x           % positionSizePercentage: 100 %          💸 positionSizeQuote:       10000 $          🆔 signalId:                     @Signal1234 | 39 | 🤖 Aleeert : Binance          🔗 Link Aleeert:             aleeert.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Aleeert ▬ Enter Long:  🔒Titan Pro👽          📱💻 Aleeert ▬ Exit Long:    🔒Titan Pro👽          📱💻 Aleeert ▬ Enter Short: 🔒Titan Pro👽          📱💻 Aleeert ▬ Exit Short:   🔒Titan Pro👽 | 40 | 🤖 Alertatron : Binance | Bybit | Deribit | Bitmex          🔗 Link Alertatron:         alertatron.com          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Alertatron ▬ Enter Long:  🔒Titan Pro👽          📱💻 Alertatron ▬ Exit Long:    🔒Titan Pro👽          📱💻 Alertatron ▬ Enter Short: 🔒Titan Pro👽          📱💻 Alertatron ▬ Exit Short:   🔒Titan Pro👽 | 41 | 🤖 Uniswap-v3          🔗 Link Alertatron:         uniswap.org          🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Enter Long:  🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Exit Long:    🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Enter Short: 🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Exit Short:   🔒Titan Pro👽 | 42 | 🧲🤖 Copy-Trading : Zignaly | Wundertrading          🔗 Link 📚 Copy-Trading:                  🔒Titan Pro👽          🧲🤖 Copy-Trading ▬ Zignaly:           🔒Titan Pro👽          🧲🤖 Copy-Trading ▬ Wundertrading: 🔒Titan Pro👽 | 43 | ♻️ ® Don't Repaint!          ♻️ This Strategy does not Repaint!:                  ® Signs Do not repaint❕          ♻️ This is a Real Strategy!:                              Quality : ® Titan Investimentos          📋️️ Get more information about Repainting here: | 44 | 🔒 Copyright ©️          🔒 Copyright ©️: Copyright © 2023-2024 All rights reserved, ® Titan Investimentos          🔒 Copyright ©️: ® Titan Investimentos          🔒 Copyright ©️: Unique and Exclusive Strategy. All rights reserved | 45 | 🏛️ Be a Titan Members          🏛️ Titan Pro        👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO)           🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission                                                                                             | 46 | ⏱ Time Left          Time Left Titan Demo 🐄: ⏱♾            | ⏱ : ♾ Titan Demo 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available          Time Left Titan Pro     👽: 🔒Titan Pro👽 | ⏱ : Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. (👽 Pro 🅼 Monthly, 👽 Pro 🆀 Quarterly, 👽 Pro🅰 Annual, 👽 Pro👾Two Years) | 47 | Nº Active Users          Nº Active Subscribers Titan Pro 👽: 5️⃣6️⃣ | 1✔️ 5✔️ 10✔️ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator)          Nº Active Affiliates    Titan Aff 🛸: 6️⃣     | 1✔️ 5✔️ 10❌ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator) 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: 🆑 Conservative: 🎯 TP=2.7 % | 🛑 SL=2.7 % • 📆All years: 🆑 Conservative: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 1669.89 % 💲   + 166989.43 USD Total Close Trades: ⚪️ 369 Percent Profitable: 🟡 64.77 % Profit Factor: 🟢 2.314 DrawDrown Maximum: 🔴 -24.82 % 💲   -10221.43 USD Avg Trade: 💲   + 452.55 USD ✔️ Trades Winning: 239 ❌ Trades Losing:   130 ✔️ Average Gross Win: + 12.31 % ❌ Average Gross Loss: - 9.78 % ✔️ Maximum Consecutive Wins:   9 ❌ Maximum Consecutive Losses: 6 %  Average Gain Annual:   499.33 % %  Average Gain Monthly: 41.61 % %  Average Gain Weekly:  9.6 % %  Average Gain Day:      1.37 % 💲  Average Gain Annual:   49933 $ 💲  Average Gain Monthly: 4161 $ 💲  Average Gain Weekly:  960 $ 💲  Average Gain Day:      137 $ • 📆 Year: 2020: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🆑 Conservative: 🚀 Leverage 1️⃣x 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: Ⓜ️ Moderate: 🎯 TP=2.8 % | 🛑 SL=2.7 % • 📆 All years: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 1472.04 % 💲   + 147199.89 USD Total Close Trades: ⚪️ 362 Percent Profitable: 🟡 63.26 % Profit Factor: 🟢 2.192 DrawDrown Maximum: 🔴 -22.69 % 💲   -9269.33 USD Avg Trade: 💲   + 406.63 USD ✔️ Trades Winning: 229 ❌ Trades Losing  : 133 ✔️ Average Gross Win: + 11.82 % ❌ Average Gross Loss: - 9.29 % ✔️ Maximum Consecutive Wins:   9 ❌ Maximum Consecutive Losses: 8 %  Average Gain Annual:  440.15 % %  Average Gain Monthly: 36.68 % %  Average Gain Weekly:  8.46 % %  Average Gain Day:      1.21 % 💲  Average Gain Annual:  44015 $ 💲  Average Gain Monthly: 3668 $ 💲  Average Gain Weekly:  846 $ 💲  Average Gain Day:      121 $ • 📆 Year: 2020: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2021: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2022: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: 🅰 Aggressive: 🎯 TP=1.6 % | 🛑 SL=6.9 % • 📆 All years: 🅰 Aggressive: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 989.38 % 💲   + 98938.38 USD Total Close Trades: ⚪️ 380 Percent Profitable: 🟢 84.47 % Profit Factor: 🟢 2.156 DrawDrown Maximum: 🔴 -17.88 % 💲   -9182.84 USD Avg Trade: 💲   + 260.36 USD ✔️ Trades Winning: 321 ❌ Trades Losing:   59 ✔️ Average Gross Win: + 5.75 % ❌ Average Gross Loss: - 14.51 % ✔️ Maximum Consecutive Wins:   21 ❌ Maximum Consecutive Losses: 6 %  Average Gain Annual:  295.84 % %  Average Gain Monthly: 24.65 % %  Average Gain Weekly:  5.69 % %  Average Gain Day:      0.81 % 💲  Average Gain Annual:  29584 $ 💲  Average Gain Monthly: 2465 $ 💲  Average Gain Weekly:  569 $ 💲  Average Gain Day:      81 $ • 📆 Year: 2020: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🅰 Aggressive: 🚀 Leverage 1️⃣x 3️⃣0️⃣ : 🛠️ Roadmap 🛠️• 14/ 01 /2023 : Titan THEMIS Launch 🛠️• Updates January/2023 :     • 📚 Tutorials for Automation 🤖 already Available : ✔️     • ✔️ Discord     • ✔️ Wundertrading     • ✔️ Zignaly     • 📚 Tutorials for Automation 🤖 In Preparation : ⭕     • ⭕ Telegram     • ⭕ Twitter     • ⭕ 3comnas     • ⭕ Aleeert     • ⭕ Alertatron     • ⭕ Uniswap-v3     • ⭕ Copy-Trading 🛠️• Updates February/2023 :     • 📰 Launch of advertising material for Titan Affiliates 🛸     • 🛍️🎥🖼️📊 (Sales Page/VSL/Videos/Creative/Infographics) 🛠️• 28/05/2023 : Titan THEMIS update ▬ Version 2.7 🛠️• 28/05/2023 : BOT BOB release ▬ Version 1.0     • (Native Titan THEMIS Automation - Through BOT BOB, a bot for automation of signals, indicators and strategies of TradingView, of own code ▬ in validation.     • BOT BOB        Automation/Connection :     • API - For Centralized Brokers.     • Smart Contracts - Wallet Web - For Decentralized Brokers.     • This way users can automate any indicator or strategy of TradingView and Titan in a decentralized, secure and simplified way.     • Without having the need to use 'third party services' for automating TradingView indicators and strategies like the ones available above. 🛠️• 28/05/2023 : Release ▬ Titan Culture Guide 📝 3️⃣1️⃣ : 🧻 Notes ❕ 🧻 • Note ❕ The "Demo 🐄" version, ❌does not have 'integrated automation', to automate the signals of this strategy and enjoy a fully automated system, you need to have access to the Pro version with '100% integrated automation' and all the tutorials for automation available. Become a Titan Pro 👽 🧻 • Note ❕ You will also need to be a "Pro User or higher on Tradingview", to be able to use the webhook feature available only for 'paid' profiles on the platform. With the webhook feature it is possible to send the signals of this strategy to almost anywhere, in our case to centralized or decentralized brokerages, also to popular messaging services such as: Discord, Telegram or Twiter. 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 🚨 • Disclaimer ❕❕ Past positive result and performance of a system does not guarantee its positive result and performance for the future! 🚨 • Disclaimer ❗❗❗ When using this strategy: Titan Investments is totally Exempt from any claim of liability for losses. The responsibility on the management of your funds is solely yours. This is a very high risk/volatility market! Understand your place in the market. 3️⃣3️⃣ : ♻️ ® No Repaint This Strategy does not Repaint! This is a real strategy! 3️⃣4️⃣ : 🔒 Copyright ©️ Copyright © 2022-2023 All rights reserved, ® Titan Investimentos 3️⃣5️⃣ : 👏 Acknowledgments I want to start this message in thanks to TradingView and all the Pinescript community for all the 'magic' created here, a unique ecosystem! rich and healthy, a fertile soil, a 'new world' of possibilities, for a complete deepening and improvement of our best personal skills. I leave here my immense thanks to the whole community: Tradingview, Pinecoders, Wizards and Moderators. I was not born Rich . Thanks to TradingView and pinescript and all its transformation. I could develop myself and the best of me and the best of my skills. And consequently build wealth and patrimony. Gratitude. One more story for the infinite book ! If you were born poor you were born to be rich ! Raising🔼 the level and raising🔼 the ruler! 📏 My work is my 'debauchery'! Do better! 💐🌹 Soul of a first-timer! Creativity Exudes! 🦄 This is the manifestation of God's magic in me. This is the best of me. 🧙 You will copy me, I know. So you owe me. 💋 My mission here is to raise the consciousness and self-esteem of all Titans and Titanids! Welcome! 🧘 🏛️ The only way to accomplish great work is to do what you love ! Before I learned to program I was wasting my life! Death is the best creation of life . Now you are the new , but in the not so distant future you will gradually become the old . Here I stay forever! Playing the game like an Athlete! 🖼️ Enjoy and Enjoy 🍷 🗿 In honor of: BOB ☆ 1 name, 3 letters, 3 possibilities, and if read backwards it's the same thing, a palindrome. ☘ Gratitude to the oracles that have enabled me the 'luck' to get this far: Dal&Ni&Fer 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView House Rules : This publication and strategy follows all TradingView house guidelines and rules: 📺 TradingView House Rules: www.tradingview.com 📺 Script publication rules:    www.tradingview.com 📺 Vendor requirements:      www.tradingview.com 📺 Links/References rules:    www.tradingview.com 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 🟩 Titan Pro 👽 🟩          3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 🟥 Titan Affiliate 🛸 🟥  
Стратегия Pine Script®
от DiFlip
1
Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4hInvestment Strategy (Quantitative Trading) | 🛑 | Watch "LIVE" and 'COPY' this strategy in real time:           🔗 Link: www.tradingview.com Hello, welcome, feel free 🌹💐 Since the stone age to the most technological age, one thing has not changed, that which continues impress human beings the most, is the other human being! Deep down, it's all very simple or very complicated, depends on how you look at it. I believe that everyone was born to do something very well in life. But few are those who have, let's use the word 'luck' . Few are those who have the 'luck' to discover this thing. That is why few are happy and successful in their jobs and professions. Thank God I had this 'luck' , and discovered what I was born to do well. And I was born to program. 👨‍💻 📋 Summary : Project Titan 0️⃣     : 🦄 Project Titan 1️⃣     : ⚖️ Quantitative THEMIS 2️⃣     : 🏛️ Titan Community 3️⃣     : 👨‍💻 Who am I ❔ 4️⃣     : ❓ What is Statistical/Probabilistic Trading ❓ 5️⃣     : ❓ How Statistical/Probabilistic Trading works ❓ 6️⃣     : ❓ Why use a Statistical/Probabilistic system ❓ 7️⃣     : ❓ Why the human brain is not prepared to do Trading ❓ 8️⃣     : ❓ What is Backtest ❓ 9️⃣     : ❓ How to build a Consistent system ❓ 🔟     : ❓ What is a Quantitative Trading system ❓ 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ 1️⃣4️⃣ : 🔧 Fixed Technical 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) 1️⃣6️⃣ : ⚠️ Risk Profile 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) 1️⃣8️⃣ : 💸 Initial Capital 1️⃣9️⃣ : ⚙️ Entry Options 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' 2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 3️⃣0️⃣ : 🛠️ Roadmap 3️⃣1️⃣ : 🧻 Notes ❕ 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 3️⃣3️⃣ : ♻️ ® No Repaint 3️⃣4️⃣ : 🔒 Copyright ©️ 3️⃣5️⃣ : 👏 Acknowledgments 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 0️⃣ : 🦄 Project Titan This is the first real, 100% automated Quantitative Strategy made available to the public and the pinescript community for TradingView. You will be able to automate all signals of this strategy for your broker , centralized or decentralized and also for messaging services : Discord, Telegram or Twitter . This is the first strategy of a larger project, in 2023, I will provide a total of 6 100% automated 'Quantitative' strategies to the pinescript community for TradingView. The future strategies to be shared here will also be unique , never before seen, real 'Quantitative' bots with real, validated results in real operation. Just like the 'Quantitative THEMIS' strategy, it will be something out of the loop throughout the pinescript/tradingview community, truly unique tools for building mutual wealth consistently and continuously for our community. 1️⃣ : ⚖️ Quantitative THEMIS : Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h This is a truly unique and out of the curve strategy for BTC /USD . A truly real strategy, with real, validated results and in real operation. A unique tool for building mutual wealth, consistently and continuously for the members of the Titan community. Initially we will operate on a monthly, quarterly, annual or biennial subscription service. Our goal here is to build a great community, in exchange for an extremely fair value for the use of our truly unique tools, which bring and will bring real results to our community members. With this business model it will be possible to provide all Titan users and community members with the purest and highest degree of sophistication in the market with pinescript for tradingview, providing unique and truly profitable strategies. My goal here is to offer the best to our members! The best 'pinescript' tradingview service in the world! We are the only Start-Up in the world that will decentralize real and full access to truly real 'quantitative' tools that bring and will bring real results for mutual and ongoing wealth building for our community. 2️⃣ : 🏛️ Titan Community : 👽 Pro 🔁 Aff 🛸 Become a Titan Pro 👽 To get access to the strategy: "Quantitative THEMIS" , and future Titan strategies in a 100% automated way, along with all tutorials for automation. Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. 👽 Pro 🅼 Monthly 👽 Pro 🆀 Quarterly 👽 Pro🅰 Annual 👽 Pro👾Two Years You will have access to a truly unique system that is out of the curve . A 100% real, 100% automated, tested, validated, profitable, and in real operation strategy. Become a Titan Affiliate 🛸 By becoming a Titan Affiliate 🛸, you will automatically receive 50% of the value of each new subscription you refer . You will receive 50% for any of the above plans that you refer . This way we will encourage our community to grow in a fair and healthy way, because we know what we have in our hands and what we deliver real value to our users. We are at the highest level of sophistication in the market, the consistency here and the results here speak for themselves. So growing our community means growing mutual wealth and raising collective conscience. Wealth must be created not divided. And here we are creating mutual wealth on all ends and in all ways. A non-zero sum system, where everybody wins. 3️⃣ : 👨‍💻 Who am I ❔ My name is FilipeSoh I am 26 years old, Technical Analyst, Trader, Computer Engineer, pinescript Specialist, with extensive experience in several languages and technologies. For the last 4 years I have been focusing on developing, editing and creating pinescript indicators and strategies for Tradingview for people and myself. Full-time passionate workaholic pinescript developer with over 10,000 hours of pinescript development. • Pinescript expert ▬Tradingview. • Specialist in Automated Trading • Specialist in Quantitative Trading. • Statistical/Probabilistic Trading Specialist - Mark Douglas Scholl. • Inventor of the 'Classic Forecast' Indicators. • Inventor of the 'Backtest Table'. 4️⃣ : ❓ What is Statistical/Probabilistic Trading ❓ Statistical/probabilistic trading is the only way to get a positive mathematical expectation regarding the market and consequently that is the only way to make money consistently from it. I will present below some more details about the Quantitative THEMIS strategy, it is a real strategy, tested, validated and in real operation, 'Skin in the Game' , a consistent way to make money with statistical/probabilistic trading in a 100% automated. I am a Technical Analyst , I used to be a Discretionary Trader , today I am 100% a Statistical Trader . I've gotten rich and made a lot of money, and I've also lost a lot with 'leverage'. That was a few years ago. The book that changed everything for me was "Trading in The Zone" by Mark Douglas. That's when I understood that the market is just a game of statistics and probability, like a casino! It was then that I understood that the human brain is not prepared for trading, because it involves triggers and mental emotions. And emotions in trading and in making trading decisions do not go well together, not in the long run, because you always have the burden of being wrong with the outcome of that particular position. But remembering that the market is just a statistical game! 5️⃣ : ❓ How Statistical/Probabilistic Trading works ❓ Let's use a 'coin' as an example: If we toss a 'coin' up 10 times. Do you agree that it is impossible for us to know exactly the result of the 'plays' before they actually happen? As in the example above, would you agree, that we cannot "guess" the outcome of a position before it actually happens? As much as we cannot "guess" whether the coin will drop heads or tails on each flip. We can analyze the "backtest" of the 10 moves made with that coin: If we analyze the 10 moves and count the number of times the coin fell heads or tails in a specific sequence, we then have a percentage of times the coin fell heads or tails, so we have a 'backtest' of those moves. Then on the next flip we can now assume a point or a favorable position for one side, the side with the highest probability . In a nutshell, this is more or less how probabilistic statistical trading works. As Statistical Traders we can never say whether such a Trader/Position we take will be a winner or a loser. But still we can have a positive and consistent result in a "sequence" of trades, because before we even open a position, backtests have already been performed so we identify an anomaly and build a system that will have a positive statistical advantage in our favor over the market. The advantage will not be in one trade itself, but in the "sequence" of trades as a whole! Because our system will work like a casino, having a positive mathematical expectation relative to the players/market. Design, develop, test models and systems that can take advantage of market anomalies, until they change. Be the casino! - Mark Douglas 6️⃣ : ❓ Why use a Statistical/Probabilistic system ❓ In recent years I have focused and specialized in developing 100% automated trading systems, essentially for the cryptocurrency market. I have developed many extremely robust and efficient systems, with positive mathematical expectation towards the market. These are not complex systems per se , because here we want to avoid 'over-optimization' as much as possible. As Da Vinci said: "Simplicity is the highest degree of sophistication". I say this because I have tested, tried and developed hundreds of systems/strategies. I believe I have programmed more than 10,000 unique indicators/strategies, because this is my passion and purpose in life. I am passionate about what I do, completely! I love statistical trading because it is the only way to get consistency in the long run! This is why I have studied, applied, developed, and specialized in 100% automated cryptocurrency trading systems. The reason why our systems are extremely "simple" is because, as I mentioned before, in statistical trading we want to exploit the market anomaly to the maximum, that is, this anomaly will change from time to time, usually we can exploit a trading system efficiently for about 6 to 12 months, or for a few years, that is; for fixed 'scalpers' systems. Because at some point these anomalies will be identified , and from the moment they are identified they will be exploited and will stop being anomalies . With the system presented here; you can even copy the indicators and input values shared here; However; what I have to offer you is: it is me , our team , and our community ! That is, we will constantly monitor this system, for life , because our goal here is to create a unique , perpetual , profitable , and consistent system for our community. Myself , our team and our community will keep this script periodically updated , to ensure the positive mathematical expectation of it. So we don't mind sharing the current parameters and values , because the real value is also in the future updates that this system will receive from me and our team , guided by our culture and our community of real users ! As we are hosted on 'tradingview', all future updates for this strategy, will be implemented and updated automatically on your tradingview account. What we want here is: to make sure you get gains from our system, because if you get gains , our ecosystem will grow as a whole in a healthy and scalable way, so we will be generating continuous mutual wealth and raising the collective consciousness . People Need People: 3️⃣🅿 7️⃣ : ❓ Why the human brain is not prepared to do Trading ❓ Today my greatest skill is to develop statistically profitable and 100% automated strategies for 'pinescript' tradingview. Note that I said: 'profitable' because in fact statistical trading is the only way to make money in a 'consistent' way from the market. And consequently have a positive wealth curve every cycle, because we will be based on mathematics, not on feelings and news. Because the human brain is not prepared to do trading. Because trading is connected to the decision making of the cerebral cortex. And the decision making is automatically linked to emotions, and emotions don't match with trading decision making, because in those moments, we can feel the best and also the worst sensations and emotions, and this certainly affects us and makes us commit grotesque mistakes! That's why the human brain is not prepared to do trading. If you want to participate in a fully automated, profitable and consistent trading system; be a Titan Pro 👽 I believe we are walking an extremely enriching path here, not only in terms of financial returns for our community, but also in terms of knowledge about probabilistic and automated statistical trading. You will have access to an extremely robust system, which was built upon very strong concepts and foundations, and upon the world's main asset in a few years: Bitcoin . We are the tip of the best that exists in the cryptocurrency market when it comes to probabilistic and automated statistical trading. Result is result! Me being dressed or naked. This is just the beginning! But there is a way to consistently make money from the market. Being the Casino! - Mark Douglas 8️⃣ : ❓ What is Backtest ❓ Imagine the market as a purely random system, but even in 'randomness' there are patterns. So now imagine the market and statistical trading as follows: Repeating the above 'coin' example, let's think of it as follows: If we toss a coin up 10 times again. It is impossible to know which flips will have heads or tails, correct? But if we analyze these 10 tosses, then we will have a mathematical statistic of the past result, for example, 70 % of the tosses fell 'heads'. That is: 7 moves fell on "heads" . 3 moves fell on "tails" . So based on these conditions and on the generic backtest presented here, we could adopt " heads " as our system of moves, to have a statistical and probabilistic advantage in relation to the next move to be performed. That is, if you define a system, based on backtests , that has a robust positive mathematical expectation in relation to the market you will have a profitable system. For every move you make you will have a positive statistical advantage in your favor over the market before you even make the move. Like a casino in relation to all its players! The casino does not have an advantage over one specific player, but over all players, because it has a positive mathematical expectation about all the moves that night. The casino will always have a positive statistical advantage over its players. Note that there will always be real players who will make real, million-dollar bankrolls that night, but this condition is already built into the casino's 'strategy', which has a pre-determined positive statistical advantage of that night as a whole. Statistical trading is the same thing, as long as you don't understand this you will keep losing money and consistently. 9️⃣ : ❓ How to build a Consistent system ❓ See most traders around the world perform trades believing that that specific position taken will make them filthy rich, because they simply believe faithfully that the position taken will be an undoubted winner, based on a trader's methodology: 'trading a trade' without analyzing the whole context, just using 'empirical' aspects in their system. But if you think of trading, as a sequence of moves. You see, 'a sequence' ! When we think statistically, it doesn't matter your result for this , or for the next specific trade , but the final sequence of trades as a whole. As the market has a random system of results distribution , if your system has a positive statistical advantage in relation to the market, at the end of that sequence you'll have the biggest probability of having a winning bank. That's how you do real trading! And with consistency! Trading is a long term game, but when you change the key you realize that it is a simple game to make money in a consistent way from the market, all you need is patience. Even more when we are based on Bitcoin, which has its 'Halving' effect where, in theory, we will never lose money in 3 to 4 years intervals, due to its scarcity and the fact that Bitcoin is the 'discovery of digital scarcity' which makes it the digital gold, we believe in this thesis and we follow Satoshi's legacy. So align Bitcoin with a probabilistic statistical trading system with a positive mathematical expectation of the market and 100% automated with the long term, and all you need is patience, and you will become rich. In fact Bitcoin by itself is already a path, buy, wait for each halving and your wealth will be maintained. No inflation, unlike fiat currencies. This is a complete and extremely robust strategy, with the most current possible and 'not possible' techniques involved and applied here. Today I am at another level in developing 100% automated 'quantitative' strategies. I was born for this! 🔟 : ❓ What is a Quantitative Trading system ❓ In addition to having access to a revolutionary strategy you will have access to disruptive 100% multifunctional tables with the ability to perform 'backtests' for better tracking and monitoring of your system on a customized basis. I would like to emphasize one thing, and that is that you keep this in mind. Today my greatest skill in 'pinescript' is to build indicators, but mainly strategies, based on statistical and probabilistic trading, with a postive mathematical expectation in relation to the market, in a 100% automated way. This with the goal of building a consistent and continuous positive equity curve through mathematics using data, converting it into statistical / probabilistic parameters and applying them to a Quantitative model. Before becoming a Quantitative Trader , I was a Technical Analyst and a Discretionary Trader . First as a position trader and then as a day trader. Before becoming a Trader, I trained myself as a Technical Analyst , to masterly understand the shape and workings of the market in theory. But everything changed when I met 'Mark Douglas' , when I got to know his works, that's when my head exploded 🤯, and I started to understand the market for good! The market is nothing more than a 'random' system of distributing results. See that I said: 'random' . Do yourself a mental exercise. Is there really such a thing as random ? I believe not, as far as we know maybe the 'singularity'. So thinking this way, to translate, the market is nothing more than a game of probability, statistics and pure mathematics. Like a casino! What happens is that most traders, whenever they take a position, take it with all the empirical certainty that such position will win or lose, and do not take into consideration the total sequence of results to understand their place in the market. Understanding your place in the market gives you the ability to create and design systems that can exploit the present market anomaly, and thus make money statistically, consistently, and 100% automated. Thinking of it this way, it is easy to make money from the market. There are many ways to make money from the market, but the only consistent way I know of is through 'probabilistic and automated statistical trading'. 1️⃣1️⃣ : ❓ How to build a Quantitative Trading system ❓ There are some fundamental points that must be addressed here in order to understand what makes up a system based on statistics and probability applied to a quantitative model. When we talk about 'discretionary' trading, it is a trading system based on human decisions after the defined 'empirical' conditions are met. It is quite another thing to build a fully automated system without any human interference/interaction . That said: Building a statistically profitable system is perfectly possible, but this is a high level task , but with possible high rewards and consistent gains. Here you will find a real "Skin In The Game" strategy. With all due respect, but the vast majority of traders who post strategies on TradingView do not understand what they are doing. Most of them do not understand the minimum complexity involved in the main variable for the construction of a real strategy, the mother variable: "strategy". I say this by my own experience, because I have analyzed practically all the existing publications of TradingView + 200,000 indicators and strategies. I breathe pinescript, I eat pinescript, I sleep pinescript, I bathe pinescript, I live TradingView. But the main advantage for the TradingView users, is that all entry and exit orders made by this strategy can be checked and analyzed thoroughly, to validate and prove the veracity of this strategy, because this is a 100% real strategy. Here there is a huge world of possibilities, but only one way to build a 'pinescript strategy' that will work correctly aligned to the real world with real results . There are some fundamental points to take into consideration when building a profitable trading system: The most important of these for me is: 'DrawDown' . Followed by: 'Hit Rate' . And only after that we use the parameter: 'Profit'. See, this is because here, we are dealing with the 'imponderable' , and anything can happen in this scenario. But there is one thing that makes us sleep peacefully at night, and that is: controlling losses . That is, in other words: controlling the DrawDown . The amateur is concerned with 'winning', the professional is concerned with conserving capital. If we have the losses under control, then we can move on to the other two parameters: hit rate and profit. See, the second most important factor in building a system is the hit rate. I say this from my own experience. I have worked with many systems with a 'low hit rate', but extremely profitable. For example: systems with hit rates of 40 to 50%. But as much as statistically and mathematically the profit is rewarding, operating systems with a low hit rate is always very stressful psychologically. That's why there are two big reasons why when I build an automated trading system, I focus on the high hit rate of the system, they are 1 - To reduce psychological damage as much as possible . 2 - And more important , when we create a system with a 'high hit rate' , there is a huge intrinsic advantage here, that most statistic traders don't take in consideration. That is: knowing more quickly when the system stops being functional. The main advantage of a system with a high hit rate is: to identify when the system stops being functional and stop exploiting the market's anomaly. Look: When we are talking about trading and random distribution of results on the market, do you agree that when we create a trading system, we are focused on exploring some anomaly of that market? When that anomaly is verified by the market, it will stop being functional with time. That's why trading systems, 'scalpers', especially for cryptocurrencies, need constant monitoring, quarterly, semi-annually or annually. Because market movements change from time to time. Because we go through different cycles from time to time, such as congestion cycles, accumulation , distribution , volatility , uptrends and downtrends . 1️⃣2️⃣ : ❓ How to Exploit Market Anomalies ❓ You see there is a very important point that must be stressed here. As we are always trying to exploit an 'anomaly' in the market. So the 'number' of indicators/tools that will integrate the system is of paramount importance. But most traders do not take this into consideration. To build a professional, robust, consistent, and profitable system, you don't need to use hundreds of indicators to build your setup. This will actually make it harder to read when the setup stops working and needs some adjustment. So focusing on a high hit rate is very important here, this is a fundamental principle that is widely ignored , and with a high hit rate, we can know much more accurately when the system is no longer functional much faster. As Darwin said: "It is not the strongest or the most intelligent that wins the game of life, it is the most adapted. So simple systems, as contradictory as it may seem, are more efficient, because they help to identify inflection points in the market much more quickly. 1️⃣3️⃣ : ❓ What Defines a Robust, Profitable and Consistent System ❓ See I have built, hundreds of thousands of indicators and 'pinescript' strategies, hundreds of thousands. This is an extremely professional, robust and profitable system. Based on the currency pairs: BTC /USDT There are many ways and avenues to build a profitable trading setup/system. And actually this is not a difficult task, taking in consideration, as the main factor here, that our trading and investment plan is for the long term, so consequently we will face scenarios with less noise. He who is in a hurry eats raw. As mentioned before. Defining trends in pinescript is technically a simple task, the hardest task is to determine congestion zones with low volume and volatility, it's in these moments that many false signals are generated, and consequently is where most setups face their maximum DrawDown. That's why this strategy was strictly and thoroughly planned, built on a very solid foundation, to avoid as much noise as possible, for a positive and consistent equity curve in each market cycle, 'Consistency' is our 'Mantra' around here. 1️⃣4️⃣ : 🔧 Fixed Technical • Strategy:      Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h • Pair:             BTC/USDTP • Time Frame: 4 hours • Broker:         Binance (Recommended) For a more conservative scenario, we have built the Quantitative THEMIS for the 4h time frame, with the main focus on consistency. So we can avoid noise as much as possible! 1️⃣5️⃣ : ❌ Fixed Outputs : 🎯 TP(%) & 🛑SL(%) In order to build a 'perpetual' system specific to BTC/USDT, it took a lot of testing, and more testing, and a lot of investment and research. There is one initial and fundamental point that we can address to justify the incredible consistency presented here. That fundamental point is our exit via Take Profit or Stop Loss percentage (%). 🎯 Take Profit (%) 🛑 Stop Loss (%) See, today I have been testing some more advanced backtesting models for some cryptocurrency systems. In which I perform 'backtest of backtest', i.e. we use a set of strategies each focused on a principle, operating individually, but they are part of something unique, i.e. we do 'backtests' of 'backtests' together. What I mean is that we do a lot of backtesting around here. I can assure you, that always the best output for a trading system is to set fixed output values! In other words: 🎯 Take Profit (%) 🛑 Stop Loss (%) This happens because statistically setting fixed exit structures in the vast majority of times, presents a superior result on the capital/equity curve, throughout history and for the vast majority of setups compared to other exit methods. This is due to a mathematical principle of simplicity, 'avoiding more noise'. Thus whenever the Quantitative THEMIS strategy takes a position it has a target and a defined maximum stop percentage. 1️⃣6️⃣ : ⚠️ Risk Profile The strategy, currently has 3 risk profiles ⚠️ patterns for 'fixed percentage exits': Take Profit (%) and Stop Loss (%) . They are: ⚠️ Rich's Profiles ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 % ❌Ⓜ️ Moderate:     🎯 TP=2.8 % 🛑 SL=2.7 % ❌🅰 Aggressive:    🎯 TP=1.6 % 🛑 SL=6.9 % You will be able to select and switch between the above options and profiles through the 'input' menu of the strategy by navigating to the "⚠️ Risk Profile" menu. You can then select, test and apply the Risk Profile above that best suits your risk management, expectations and reality , as well as customize all the 'fixed exit' values through the TP and SL menus below. 1️⃣7️⃣ : ⭕ Moving Exits : (Indicators) The strategy currently also has 'Moving Exits' based on indicator signals. These are Moving Exits (Indicators) 📈 LONG : (EXIT) 🧃 (MAO) Short : true 📉 SHORT : (EXIT) 🧃 (MAO) Long: false You can select and toggle between the above options through the 'input' menu of the strategy by navigating to the "LONG : Exit" and "SHORT : Exit" menu. 1️⃣8️⃣ : 💸 Initial Capital By default the "Initial Capital" set for entries and backtests of this strategy is: 10000 $ You can set another value for the 'Starting Capital' through the tradingview menu under "properties" , and edit the value of the "Initial Capital" field. This way you can set and test other 'Entry Values' for your trades, tests and backtests. 1️⃣9️⃣ : ⚙️ Entry Options By default the 'order size' set for this strategy is 100 % of the 'initial capital' on each new trade. You can set and test other entry options like : contracts , cash , % of equity You should make these changes directly in the input menu of the strategy by navigating to the menu "⚙️ Properties : TradingView" below. ⚙️ Properties : (TradingView) 📊 Strategy Type:   strategy.position_size != 1 📝💲 % Order Type: % of equity 📝💲 % Order Size: 100 Leverage:             1 So you can define and test other 'Entry Options' for your trades, tests and backtests. 2️⃣0️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Third-Party Services' It is possible to automate the signals of this strategy for any centralized or decentralized broker, as well as for messaging services: Discord, Telegram and Twitter. All in an extremely simple and uncomplicated way through the tutorials available in PDF /VIDEO for our Titan Pro 👽 subscriber community. With our tutorials in PDF and Video it will be possible to automate the signals of this strategy for the chosen service in an extremely simple way with less than 10 steps only. Tradingview naturally doesn't count with native integration between brokers and tradingview. But it is possible to use 'third party services' to do the integration and automation between Tradingview and your centralized or decentralized broker. Here are the standard, available and recommended 'third party services' to automate the signals from the 'Quantitative THEMIS' strategy on the tradingview for your broker: 1) Wundertrading (Recommended): 2) 3commas:                                3) Zignaly:                                   4) Aleeert.com    (Recommended): 5) Alertatron:                               Note! 'Third party services' cannot perform 'withdrawals' via their key 'API', they can only open positions, so your funds will always be 'safe' in your brokerage firm, being traded via the 'API', when they receive an entry and exit signal from this strategy. 2️⃣1️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Exchanges You can automate this strategy for any of the brokers below, through your broker's 'API' by connecting it to the 'third party automation services' for tradingview available and mentioned in the menu above: 1) Binance (Recommended) 2) Bitmex 3) Bybit 4) KuCoin 5) Deribit 6) OKX 7) Coinbase 8) Huobi 9) Bitfinex 10) Bitget 11) Bittrex 12) Bitstamp 13) Gate. io 14) Kraken 15) Gemini 16) Ascendex 17) VCCE 2️⃣2️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : 'Messaging Services' You can also automate and monitor the signals of this strategy much more efficiently by sending them to the following popular messaging services: 1) Discord 2) Telegram 3) Twitter 2️⃣3️⃣ : ❓ How to Automate this Strategy ❓ : 🤖 Automation : '🧲🤖Copy-Trading' It will also be possible to copy/replicate the entries and exits of this strategy to your broker in an extremely simple and agile way, through the available copy-trader services. This way it will be possible to replicate the signals of this strategy at each entry and exit to your broker through the API connecting it to the integrated copy-trader services available through the tradingview automation services below: 1) Wundetrading: 2) Zignaly:           2️⃣4️⃣ : ❔ Why be a Titan Pro 👽❔ I believe that today I am at another level in 'pinescript' development. I consider myself today a true unicorn as a pinescript developer, someone unique and very rare. If you choose another tool or another pinescript service, this tool will be just another one, with no real results. But if you join our Titan community, you will have access to a unique tool! And you will get real results! I already earn money consistently with statistical and automated trading and as an expert pinescript developer. I am here to evolve my skills as much as possible, and one day become a pinescript 'Wizard'. So excellence, quality and professionalism will always be my north here. You will never find a developer like me, and who will take so seriously such a revolutionary project as this one. A Maverick! ▬ The man never stops! Here you will find the highest degree of sophistication and development in the market for 'pinescript'. You will get the best of me and the best of pinescript possible. Let me show you how a professional in my field does it. Become a Titan Pro Member 👽 and get Full Access to this strategy and all the Automation Tutorials. Be the Titan in your life! 2️⃣5️⃣ : ❔ Why be a Titan Aff 🛸❔ Get financial return for your referrals, Decentralize the World, and raise the collective consciousness. 2️⃣6️⃣ : 📋 Summary : ⚖️ Strategy: Titan Investments|Quantitative THEMIS|Demo|BINANCE:BTCUSDTP:4h ® Titan Investimentos | Quantitative THEMIS ⚖️ | Demo 🐄 2.6 | Dev: © FilipeSoh 🧙 | 🤖 100% Automated : Discord, Telegram, Twitter, Wundertrading, 3commas, Zignaly, Aleeert, Alertatron, Uniswap-v3 | BINANCE:BTCUSDTPERP 4h 🛒 Subscribe this strategy  ❗️  Be a Titan Member 🏛️ 🛒 Titan Pro        👽  🔗 🏛️ Titan Pro        👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) 🛒 Titan Affiliate 🛸  🔗 🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission 📋 Summary : QT THEMIS ⚖️ 🕵️‍♂️ Check This Strategy..................................................................0 🦄 ® Titan Investimentos...............................................................1 👨‍💻 © Developer..........................................................................2 📚 Signal Automation Tutorials : (PDF/VIDEO).......................................3 👨‍🔧 Revision...............................................................................4 📊 Table : (BACKTEST)..................................................................5 📊 Table : (INFORMATIONS).............................................................6 ⚙️ Properties : (TRADINGVIEW)........................................................7 📆 Backtest : (TRADINGVIEW)..........................................................8 ⚠️ Risk Profile...........................................................................9 🟢 On 🔴 Off : (LONG/SHORT).......................................................10 📈 LONG : (ENTRY)....................................................................11 📉 SHORT : (ENTRY)...................................................................12 📈 LONG : (EXIT).......................................................................13 📉 SHORT : (EXIT)......................................................................14 🧩 (EI) External Indicator.............................................................15 📡 (QT) Quantitative...................................................................16 🎠 (FF) Forecast......................................................................17 🅱 (BB) Bollinger Bands................................................................18 🧃 (MAP) Moving Average Primary......................................................19 🧃 (MAP) Labels.........................................................................20 🍔 (MAQ) Moving Average Quaternary.................................................21 🍟 (MACD) Moving Average Convergence Divergence...............................22 📣 (VWAP) Volume Weighted Average Price........................................23 🪀 (HL) HILO..........................................................................24 🅾 (OBV) On Balance Volume.........................................................25 🥊 (SAR) Stop and Reverse...........................................................26 🛡️ (DSR) Dynamic Support and Resistance..........................................27 🔊 (VD) Volume Directional..........................................................28 🧰 (RSI) Relative Momentum Index.................................................29 🎯 (TP) Take Profit %..................................................................30 🛑 (SL) Stop Loss %....................................................................31 🤖 Automation Selected...............................................................32 📱💻 Discord............................................................................33 📱💻 Telegram..........................................................................34 📱💻 Twitter...........................................................................35 🤖 Wundertrading......................................................................36 🤖 3commas............................................................................37 🤖 Zignaly...............................................................................38 🤖 Aleeert...............................................................................39 🤖 Alertatron...........................................................................40 🤖 Uniswap-v3..........................................................................41 🧲🤖 Copy-Trading....................................................................42 ♻️ ® No Repaint........................................................................43 🔒 Copyright ©️..........................................................................44 🏛️ Be a Titan Member..................................................................45 Nº Active Users..........................................................................46 ⏱ Time Left............................................................................47 | 0 | 🕵️‍♂️ Check This Strategy         🕵️‍♂️ Version Demo: 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available         🕵️‍♂️ Version Pro: 👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO) | 1 | 🦄 ® Titan Investimentos         Decentralizing the World 🗺         Raising the Collective Conscience 🗺                 🦄Site:                      🦄TradingView: www.tradingview.com         🦄Discord:                 🦄Telegram:              🦄Youtube:                🦄Twitter:                 🦄Instagram:             🦄TikTok:                 🦄Linkedin:               🦄E-mail:          | 2 | 👨‍💻 © Developer         🧠 Developer:    @FilipeSoh🧙         📺 TradingView: www.tradingview.com         ☑️ Linkedin:               ✅ Fiverr:                  ✅ Upwork:                🎥 YouTube:               🐤 Twitter:                🤳 Instagram:    | 3 | 📚 Signal Automation Tutorials : (PDF/VIDEO)         📚 Discord:           🔗 Link: 🔒Titan Pro👽         📚 Telegram:        🔗 Link: 🔒Titan Pro👽         📚 Twitter:           🔗 Link: 🔒Titan Pro👽         📚 Wundertrading: 🔗 Link: 🔒Titan Pro👽         📚 3comnas:         🔗 Link: 🔒Titan Pro👽         📚 Zignaly:           🔗 Link: 🔒Titan Pro👽         📚 Aleeert:           🔗 Link: 🔒Titan Pro👽         📚 Alertatron:       🔗 Link: 🔒Titan Pro👽         📚 Uniswap-v3:     🔗 Link: 🔒Titan Pro👽         📚 Copy-Trading:   🔗 Link: 🔒Titan Pro👽 | 4 | 👨‍🔧 Revision         👨‍🔧 Start Of Operations: 01 Jan 2019 21:00 -0300 💡 Start Of Operations (Skin in the game) : Revision 1.0         👨‍🔧 Previous Review:      01 Jan 2022 21:00 -0300 💡 Previous Review : Revision 2.0         👨‍🔧 Current Revision:     01 Jan 2023 21:00 -0300 💡 Current Revision : Revision 2.6         👨‍🔧 Next Revision:         28 May 2023 21:00 -0300 💡 Next Revision : Revision 2.7 | 5 | 📊 Table : (BACKTEST)         📊 Table: true         🖌️ Style:  label.style_label_left         📐 Size:   size_small         📏 Line:  defval         🎨 Color: #131722 | 6 | 📊 Table : (INFORMATIONS)         📊 Table: false         🖌️ Style:  label.style_label_right         📐 Size:   size_small         📏 Line:  defval         🎨 Color: #131722 | 7 | ⚙️ Properties : (TradingView)         📊 Strategy Type:  strategy.position_size != 1         📝💲 % Order Type: % of equity         📝💲 % Order Size: 100 %         🚀 Leverage:        1 | 8 | 📆 Backtest : (TradingView)         🗓️ Mon:     true         🗓️ Tue:      true         🗓️ Wed:     true         🗓️ Thu:      true         🗓️ Fri:       true         🗓️ Sat:       true         🗓️ Sun:      true         📆 Range:  custom         📆 Start:    UTC 31 Oct 2008 00:00         📆 End:      UTC 31 Oct 2030 23:45         📆 Session: 0000-0000         📆 UTC:     UTC | 9 | ⚠️ Risk Profile         ✔️🆑 Conservative: 🎯 TP=2.7 % 🛑 SL=2.7 %         ❌Ⓜ️ Moderate:     🎯 TP=2.8 % 🛑 SL=2.7 %         ❌🅰 Aggressive:    🎯 TP=1.6 % 🛑 SL=6.9 % | 10 | 🟢 On 🔴 Off : (LONG/SHORT)          🟢📈 LONG:  true          🟢📉 SHORT: true | 11 | 📈 LONG : (ENTRY)          📡 (QT) Long:       true          🧃 (MAP) Long:      false          🅱 (BB) Long:       false          🍟 (MACD) Long: false          🅾 (OBV) Long:     false | 12 | 📉 SHORT : (ENTRY)          📡 (QT) Short:       true          🧃 (MAP) Short:      false          🅱 (BB) Short:       false          🍟 (MACD) Short: false          🅾 (OBV) Short:     false | 13 | 📈 LONG : (EXIT)          🧃 (MAP) Short: true | 14 | 📉 SHORT : (EXIT)          🧃 (MAP) Long: false | 15 | 🧩 (EI) External Indicator          🧩 (EI) Connect your external indicator/filter:             false          🧩 (EI) Connect your indicator here (Study mode only): close          🧩 (EI) Connect your indicator here (Study mode only): close | 16 | 📡 (QT) Quantitative          📡 (QT) Quantitative: true          📡 (QT) Market:        BINANCE:BTCUSDTPERP          📡 (QT) Dice:            openai | 17 | 🎠 (FF) Forecast          🎠 (FF) Include current unclosed current candle:  true          🎠 (FF) Forecast Type:                                    flat          🎠 (FF) Nº of candles to use in linear regression: 3 | 18 | 🅱 (BB) Bollinger Bands          🅱 (BB) Bollinger Bands: true          🅱 (BB) Type:               EMA          🅱 (BB) Period:             20          🅱 (BB) Source:            close          🅱 (BB) Multiplier:         2          🅱 (BB) Linewidth:        0          🅱 (BB) Color:              #131722 | 19 | 🧃 (MAP) Moving Average Primary          🧃 (MAP) Moving Average Primary: true          🧃 (MAP) BarColor:                      false          🧃 (MAP) Background:                  false          🧃 (MAP) Type:                           SMA          🧃 (MAP) Source:                        open          🧃 (MAP) Period:                         100          🧃 (MAP) Multiplier:                     2.0          🧃 (MAP) Linewidth:                    2          🧃 (MAP) Color P:                        #42bda8          🧃 (MAP) Color N:                       #801922 | 20 | 🧃 (MAP) Labels          🧃 (MAP) Labels:               true          🧃 (MAP) Style BUY ZONE:  shape.labelup          🧃 (MAP) Color BUY ZONE: #42bda8          🧃 (MAP) Style SELL ZONE: shape.labeldown          🧃 (MAP) Color SELL ZONE: #801922 | 21 | 🍔 (MAQ) Moving Average Quaternary          🍔 (MAQ) Moving Average Quaternary: true          🍔 (MAQ) BarColor:                          false          🍔 (MAQ) Background:                      false          🍔 (MAQ) Type:                                SMA          🍔 (MAQ) Source:                             close          🍔 (MAQ) Primary:                           14          🍔 (MAQ) Secondary:                        22          🍔 (MAQ) Tertiary:                           44          🍔 (MAQ) Quaternary:                      16          🍔 (MAQ) Linewidth:                         0          🍔 (MAQ) Color P:                            #42bda8          🍔 (MAQ) Color N:                            #801922 | 22 | 🍟 (MACD) Moving Average Convergence Divergence          🍟 (MACD) Macd Type:  EMA          🍟 (MACD) Signal Type: EMA          🍟 (MACD) Source:       close          🍟 (MACD) Fast:          12          🍟 (MACD) Slow:          26          🍟 (MACD) Smoothing:  9 | 23 | 📣 (VWAP) Volume Weighted Average Price          📣 (VWAP) Source:             close          📣 (VWAP) Period:              340          📣 (VWAP) Momentum A:     84          📣 (VWAP) Momentum B:    150          📣 (VWAP) Average Volume: 1          📣 (VWAP) Multiplier:          1          📣 (VWAP) Diviser:             2 | 24 | 🪀 (HL) HILO          🪀 (HL) Type:          SMA          🪀 (HL) Function:     Maverick🧙          🪀 (HL) Source H:    high          🪀 (HL) Source L:     low          🪀 (HL) Period:        20          🪀 (HL) Momentum: 26          🪀 (HL) Diviser:        2          🪀 (HL) Multiplier:    1 | 25 | 🅾 (OBV) On Balance Volume          🅾 (OBV) Type:        EMA          🅾 (OBV) Source:     close          🅾 (OBV) Period:     16          🅾 (OBV) Diviser:     2          🅾 (OBV) Multiplier: 1 | 26 | 🥊 (SAR) Stop and Reverse          🥊 (SAR) Source:     close          🥊 (SAR) High:        1.8          🥊 (SAR) Mid:         1.6          🥊 (SAR) Low:        1.6          🥊 (SAR) Diviser:     2          🥊 (SAR) Multiplier: 1 | 27 | 🛡️ (DSR) Dynamic Support and Resistance          🛡️ (DSR) Source D:       close          🛡️ (DSR) Source R:       high          🛡️ (DSR) Source S:       low          🛡️ (DSR) Momentum R: 0          🛡️ (DSR) Momentum S: 2          🛡️ (DSR) Diviser:          2          🛡️ (DSR) Multiplier:      1 | 28 | 🔊 (VD) Volume Directional          🔊 (VD) Type:          SMA          🔊 (VD) Period:        68          🔊 (VD) Momentum: 3.8          🔊 (VD) Diviser:       2          🔊 (VD) Multiplier:    1 | 29 | 🧰 (RSI) Relative Momentum Index          🧰 (RSI) Type UP:        EMA          🧰 (RSI) Type DOWN:   EMA          🧰 (RSI) Source:          close          🧰 (RSI) Period:           29          🧰 (RSI) Smoothing:     22          🧰 (RSI) Momentum R: 64          🧰 (RSI) Momentum S: 142          🧰 (RSI) Diviser:          2          🧰 (RSI) Multiplier:      1 | 30 | 🎯 (TP) Take Profit %          🎯 (TP) Take Profit: false          🎯 (TP) %:              2.2          🎯 (TP) Color:         #42bda8          🎯 (TP) Linewidth:  1 | 31 | 🛑 (SL) Stop Loss %          🛑 (SL) Stop Loss:  false          🛑 (SL) %:             2.7          🛑 (SL) Color:        #801922          🛑 (SL) Linewidth: 1 | 32 | 🤖 Automation : Discord | Telegram | Twitter | Wundertrading | 3commas | Zignaly | Aleeert | Alertatron | Uniswap-v3          🤖 Automation Selected : Discord | 33 | 🤖 Discord          🔗 Link Discord:                      🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Discord ▬ Enter Long:  🔒Titan Pro👽          📱💻 Discord ▬ Exit Long:    🔒Titan Pro👽          📱💻 Discord ▬ Enter Short: 🔒Titan Pro👽          📱💻 Discord ▬ Exit Short:   🔒Titan Pro👽 | 34 | 🤖 Telegram          🔗 Link Telegram:                    🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Telegram ▬ Enter Long:  🔒Titan Pro👽          📱💻 Telegram ▬ Exit Long:    🔒Titan Pro👽          📱💻 Telegram ▬ Enter Short: 🔒Titan Pro👽          📱💻 Telegram ▬ Exit Short:   🔒Titan Pro👽 | 35 | 🤖 Twitter          🔗 Link Twitter:                      🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Twitter ▬ Enter Long:  🔒Titan Pro👽          📱💻 Twitter ▬ Exit Long:    🔒Titan Pro👽          📱💻 Twitter ▬ Enter Short: 🔒Titan Pro👽          📱💻 Twitter ▬ Exit Short:   🔒Titan Pro👽 | 36 | 🤖 Wundertrading : Binance | Bitmex | Bybit | KuCoin | Deribit | OKX | Coinbase | Huobi | Bitfinex | Bitget          🔗 Link Wundertrading:            🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Wundertrading ▬ Enter Long:  🔒Titan Pro👽          📱💻 Wundertrading ▬ Exit Long:    🔒Titan Pro👽          📱💻 Wundertrading ▬ Enter Short: 🔒Titan Pro👽          📱💻 Wundertrading ▬ Exit Short:   🔒Titan Pro👽 | 37 | 🤖 3commas : Binance | Bybit | OKX | Bitfinex | Coinbase | Deribit | Bitmex | Bittrex | Bitstamp | Gate.io | Kraken | Gemini | Huobi | KuCoin          🔗 Link 3commas:                    🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 3commas ▬ Enter Long:  🔒Titan Pro👽          📱💻 3commas ▬ Exit Long:    🔒Titan Pro👽          📱💻 3commas ▬ Enter Short: 🔒Titan Pro👽          📱💻 3commas ▬ Exit Short:   🔒Titan Pro👽 | 38 | 🤖 Zignaly : Binance | Ascendex | Bitmex | Kucoin | VCCE          🔗 Link Zignaly:                       🔗 Link 📚 Automation: 🔒Titan Pro👽          🤖 Type Automation:        Profit Sharing          🤖 Type Provider:             Webook          🔑 Key:                         🔒Titan Pro👽          🤖 pair:                         BTCUSDTP          🤖 exchange:                  binance          🤖 exchangeAccountType: futures          🤖 orderType:                 market          🚀 leverage:                   1x           % positionSizePercentage: 100 %          💸 positionSizeQuote:       10000 $          🆔 signalId:                     @Signal1234 | 39 | 🤖 Aleeert : Binance          🔗 Link Aleeert:                       🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Aleeert ▬ Enter Long:  🔒Titan Pro👽          📱💻 Aleeert ▬ Exit Long:    🔒Titan Pro👽          📱💻 Aleeert ▬ Enter Short: 🔒Titan Pro👽          📱💻 Aleeert ▬ Exit Short:   🔒Titan Pro👽 | 40 | 🤖 Alertatron : Binance | Bybit | Deribit | Bitmex          🔗 Link Alertatron:                   🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Alertatron ▬ Enter Long:  🔒Titan Pro👽          📱💻 Alertatron ▬ Exit Long:    🔒Titan Pro👽          📱💻 Alertatron ▬ Enter Short: 🔒Titan Pro👽          📱💻 Alertatron ▬ Exit Short:   🔒Titan Pro👽 | 41 | 🤖 Uniswap-v3          🔗 Link Alertatron:                   🔗 Link 📚 Automation: 🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Enter Long:  🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Exit Long:    🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Enter Short: 🔒Titan Pro👽          📱💻 Uniswap-v3 ▬ Exit Short:   🔒Titan Pro👽 | 42 | 🧲🤖 Copy-Trading : Zignaly | Wundertrading          🔗 Link 📚 Copy-Trading:                  🔒Titan Pro👽          🧲🤖 Copy-Trading ▬ Zignaly:           🔒Titan Pro👽          🧲🤖 Copy-Trading ▬ Wundertrading: 🔒Titan Pro👽 | 43 | ♻️ ® Don't Repaint!          ♻️ This Strategy does not Repaint!:                  ® Signs Do not repaint❕          ♻️ This is a Real Strategy!:                              Quality : ® Titan Investimentos          📋️️ Get more information about Repainting here: | 44 | 🔒 Copyright ©️          🔒 Copyright ©️: Copyright © 2023-2024 All rights reserved, ® Titan Investimentos          🔒 Copyright ©️: ® Titan Investimentos          🔒 Copyright ©️: Unique and Exclusive Strategy. All rights reserved | 45 | 🏛️ Be a Titan Members          🏛️ Titan Pro        👽 Version with ✔️100% Integrated Automation 🤖 and 📚 Automation Tutorials ✔️100% available at: (PDF/VIDEO)           🏛️ Titan Affiliate 🛸 (Subscription Sale) 🔥 Receive 50% commission                                                                                             | 46 | ⏱ Time Left          Time Left Titan Demo 🐄: ⏱♾            | ⏱ : ♾ Titan Demo 🐄 Version with ❌non-integrated automation 🤖 and 📚 Tutorials for automation ❌not available          Time Left Titan Pro     👽: 🔒Titan Pro👽 | ⏱ : Pro Plans: 30 Days, 90 Days, 12 Months, 24 Months. (👽 Pro 🅼 Monthly, 👽 Pro 🆀 Quarterly, 👽 Pro🅰 Annual, 👽 Pro👾Two Years) | 47 | Nº Active Users          Nº Active Subscribers Titan Pro 👽: 5️⃣6️⃣ | 1✔️ 5✔️ 10✔️ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator)          Nº Active Affiliates    Titan Aff 🛸: 6️⃣     | 1✔️ 5✔️ 10❌ 100❌ 1K❌ 10K❌ 50K❌ 100K❌ 1M❌ 10M❌ 100M❌ : ⏱ Active Users is updated every 24 hours (Check on indicator) 2️⃣7️⃣ : 📊 PERFORMANCE : 🆑 Conservative 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: 🆑 Conservative: 🎯 TP=2.7 % | 🛑 SL=2.7 % • 📆All years: 🆑 Conservative: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 1669.89 % 💲   + 166989.43 USD Total Close Trades: ⚪️ 369 Percent Profitable: 🟡 64.77 % Profit Factor: 🟢 2.314 DrawDrown Maximum: 🔴 -24.82 % 💲   -10221.43 USD Avg Trade: 💲   + 452.55 USD ✔️ Trades Winning: 239 ❌ Trades Losing:   130 ✔️ Average Gross Win: + 12.31 % ❌ Average Gross Loss: - 9.78 % ✔️ Maximum Consecutive Wins:   9 ❌ Maximum Consecutive Losses: 6 %  Average Gain Annual:   499.33 % %  Average Gain Monthly: 41.61 % %  Average Gain Weekly:  9.6 % %  Average Gain Day:      1.37 % 💲  Average Gain Annual:   49933 $ 💲  Average Gain Monthly: 4161 $ 💲  Average Gain Weekly:  960 $ 💲  Average Gain Day:      137 $ • 📆 Year: 2020: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🆑 Conservative: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🆑 Conservative: 🚀 Leverage 1️⃣x 2️⃣8️⃣ : 📊 PERFORMANCE : Ⓜ️ Moderate 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: Ⓜ️ Moderate: 🎯 TP=2.8 % | 🛑 SL=2.7 % • 📆 All years: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 1472.04 % 💲   + 147199.89 USD Total Close Trades: ⚪️ 362 Percent Profitable: 🟡 63.26 % Profit Factor: 🟢 2.192 DrawDrown Maximum: 🔴 -22.69 % 💲   -9269.33 USD Avg Trade: 💲   + 406.63 USD ✔️ Trades Winning: 229 ❌ Trades Losing  : 133 ✔️ Average Gross Win: + 11.82 % ❌ Average Gross Loss: - 9.29 % ✔️ Maximum Consecutive Wins:   9 ❌ Maximum Consecutive Losses: 8 %  Average Gain Annual:  440.15 % %  Average Gain Monthly: 36.68 % %  Average Gain Weekly:  8.46 % %  Average Gain Day:      1.21 % 💲  Average Gain Annual:  44015 $ 💲  Average Gain Monthly: 3668 $ 💲  Average Gain Weekly:  846 $ 💲  Average Gain Day:      121 $ • 📆 Year: 2020: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2021: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x • 📆 Year: 2022: Ⓜ️ Moderate: 🚀 Leverage 1️⃣x 2️⃣9️⃣ : 📊 PERFORMANCE : 🅰 Aggressive 📊 Exchange:         Binance 📊 Pair:                BINANCE:  BTCUSDTPERP 📊 TimeFrame:      4h 📊 Initial Capital:   10000 $ 📊 Order Type:       % equity 📊 Size Per Order: 100 % 📊 Commission:     0.03 % 📊 Pyramid:          1 • ⚠️ Risk Profile: 🅰 Aggressive: 🎯 TP=1.6 % | 🛑 SL=6.9 % • 📆 All years: 🅰 Aggressive: 🚀 Leverage 1️⃣x 📆 Start: September 23, 2019 📆 End: January 11, 2023 📅 Days: 1221 📅 Bars:  7325 Net Profit: 🟢 + 989.38 % 💲   + 98938.38 USD Total Close Trades: ⚪️ 380 Percent Profitable: 🟢 84.47 % Profit Factor: 🟢 2.156 DrawDrown Maximum: 🔴 -17.88 % 💲   -9182.84 USD Avg Trade: 💲   + 260.36 USD ✔️ Trades Winning: 321 ❌ Trades Losing:   59 ✔️ Average Gross Win: + 5.75 % ❌ Average Gross Loss: - 14.51 % ✔️ Maximum Consecutive Wins:   21 ❌ Maximum Consecutive Losses: 6 %  Average Gain Annual:  295.84 % %  Average Gain Monthly: 24.65 % %  Average Gain Weekly:  5.69 % %  Average Gain Day:      0.81 % 💲  Average Gain Annual:  29584 $ 💲  Average Gain Monthly: 2465 $ 💲  Average Gain Weekly:  569 $ 💲  Average Gain Day:      81 $ • 📆 Year: 2020: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2021: 🅰 Aggressive: 🚀 Leverage 1️⃣x • 📆 Year: 2022: 🅰 Aggressive: 🚀 Leverage 1️⃣x 3️⃣0️⃣ : 🛠️ Roadmap 🛠️• 14/ 01 /2023 : Titan THEMIS Launch 🛠️• Updates January/2023 :     • 📚 Tutorials for Automation 🤖 already Available : ✔️     • ✔️ Discord     • ✔️ Wundertrading     • ✔️ Zignaly     • 📚 Tutorials for Automation 🤖 In Preparation : ⭕     • ⭕ Telegram     • ⭕ Twitter     • ⭕ 3comnas     • ⭕ Aleeert     • ⭕ Alertatron     • ⭕ Uniswap-v3     • ⭕ Copy-Trading 🛠️• Updates February/2023 :     • 📰 Launch of advertising material for Titan Affiliates 🛸     • 🛍️🎥🖼️📊 (Sales Page/VSL/Videos/Creative/Infographics) 🛠️• 28/05/2023 : Titan THEMIS update ▬ Version 2.7 🛠️• 28/05/2023 : BOT BOB release ▬ Version 1.0     • (Native Titan THEMIS Automation - Through BOT BOB, a bot for automation of signals, indicators and strategies of TradingView, of own code ▬ in validation.     • BOT BOB        Automation/Connection :     • API - For Centralized Brokers.     • Smart Contracts - Wallet Web - For Decentralized Brokers.     • This way users can automate any indicator or strategy of TradingView and Titan in a decentralized, secure and simplified way.     • Without having the need to use 'third party services' for automating TradingView indicators and strategies like the ones available above. 🛠️• 28/05/2023 : Release ▬ Titan Culture Guide 📝 3️⃣1️⃣ : 🧻 Notes ❕ 🧻 • Note ❕ The "Demo 🐄" version, ❌does not have 'integrated automation', to automate the signals of this strategy and enjoy a fully automated system, you need to have access to the Pro version with '100% integrated automation' and all the tutorials for automation available. Become a Titan Pro 👽 🧻 • Note ❕ You will also need to be a "Pro User or higher on Tradingview", to be able to use the webhook feature available only for 'paid' profiles on the platform. With the webhook feature it is possible to send the signals of this strategy to almost anywhere, in our case to centralized or decentralized brokerages, also to popular messaging services such as: Discord, Telegram or Twiter. 3️⃣2️⃣ : 🚨 Disclaimer ❕❗ 🚨 • Disclaimer ❕❕ Past positive result and performance of a system does not guarantee its positive result and performance for the future! 🚨 • Disclaimer ❗❗❗ When using this strategy: Titan Investments is totally Exempt from any claim of liability for losses. The responsibility on the management of your funds is solely yours. This is a very high risk/volatility market! Understand your place in the market. 3️⃣3️⃣ : ♻️ ® No Repaint This Strategy does not Repaint! This is a real strategy! 3️⃣4️⃣ : 🔒 Copyright ©️ Copyright © 2022-2023 All rights reserved, ® Titan Investimentos 3️⃣5️⃣ : 👏 Acknowledgments I want to start this message in thanks to TradingView and all the Pinescript community for all the 'magic' created here, a unique ecosystem! rich and healthy, a fertile soil, a 'new world' of possibilities, for a complete deepening and improvement of our best personal skills. I leave here my immense thanks to the whole community: Tradingview, Pinecoders, Wizards and Moderators. I was not born Rich . Thanks to TradingView and pinescript and all its transformation. I could develop myself and the best of me and the best of my skills. And consequently build wealth and patrimony. Gratitude. One more story for the infinite book ! If you were born poor you were born to be rich ! Raising🔼 the level and raising🔼 the ruler! 📏 My work is my 'debauchery'! Do better! 💐🌹 Soul of a first-timer! Creativity Exudes! 🦄 This is the manifestation of God's magic in me. This is the best of me. 🧙 You will copy me, I know. So you owe me. 💋 My mission here is to raise the consciousness and self-esteem of all Titans and Titanids! Welcome! 🧘 🏛️ The only way to accomplish great work is to do what you love ! Before I learned to program I was wasting my life! Death is the best creation of life . Now you are the new , but in the not so distant future you will gradually become the old . Here I stay forever! Playing the game like an Athlete! 🖼️ Enjoy and Enjoy 🍷 🗿 In honor of: BOB ☆ 1 name, 3 letters, 3 possibilities, and if read backwards it's the same thing, a palindrome. ☘ Gratitude to the oracles that have enabled me the 'luck' to get this far: Dal&Ni&Fer 3️⃣6️⃣ : 👮 House Rules : 📺 TradingView House Rules : This publication and strategy follows all TradingView house guidelines and rules: 📺 TradingView House Rules: www.tradingview.com 📺 Script publication rules:    www.tradingview.com 📺 Vendor requirements:      www.tradingview.com 📺 Links/References rules:    www.tradingview.com 3️⃣7️⃣ : 🏛️ Become a Titan Pro member 👽 🟩 Titan Pro 👽 🟩          3️⃣8️⃣ : 🏛️ Be a member Titan Aff 🛸 🟥 Titan Affiliate 🛸 🟥  
Стратегия Pine Script®
от DiFlip
11
TradingView.To Strategy Template (with Dyanmic Alerts)Hello traders, If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further. This Pine Script v5 strategy template is engineered for maximum customization and risk management. Best part? This Pine Script v5 template facilitates the dynamic construction of TradingView.TO alerts, sparing users the time and effort of mastering the TradingView.TO syntax and manually create alert commands. This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via TradingView.TO bot. IMPORTANT NOTES TradingView.TO is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, Metatrader 4/5, ...) for automating trading. Many traders don't know how to create TradingView.TO dynamically-compatible alerts using the data from their TradingView scripts. Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly. This script showcases how to create TradingView.TO alerts dynamically. TRADINGVIEW ALERTS 1) You'll have to create one alert per asset X timeframe = 1 chart. Example: 1 alert for BTC/USDT on the 5 minutes chart, 1 alert for BTC/USDT on the 15-minute chart (assuming you want your bot to trade the BTC/USDT on the 5 and 15-minute timeframes) 2) Select the Order fills and alert() function calls condition 3) For each alert, the alert message is pre-configured with the text below {{strategy.order.alert_message}} Please leave it as it is. It's a TradingView native variable that will fetch the alert text messages built by the script. 4) TradingView.TO uses webhook technology - setting a webhook URL from the alerts notifications tab is required. KEY FEATURES I) Modular Indicator Connection * plug your existing indicator into the template. * Only two lines of code are needed for full compatibility. Step 1: Create your connector Adapt your indicator with only 2 lines of code and then connect it to this strategy template. To do so: 1) Find in your indicator where the conditions print the long/buy and short/sell signals. 2) Create an additional plot as below I'm giving an example with a Two moving averages cross. Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions. //@version=5 indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true) atrPeriod = input.int(10, "ATR Length", minval = 1) factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01) = ta.supertrend(factor, atrPeriod) supertrend := barstate.isfirst ? na : supertrend bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none) upTrend = plot(direction &lt; 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr) downTrend = plot(direction &lt; 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr) fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false) fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false) buy = ta.crossunder(direction, 0) sell = ta.crossunder(direction, 0) //////// CONNECTOR SECTION //////// Signal = buy ? 1 : sell ? -1 : 0 plot(Signal, title = "Signal", display = display.data_window) //////// CONNECTOR SECTION //////// Important Notes 🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal Now, you can connect your indicator to the Strategy Template using the method below or that one. Step 2: Connect the connector 1) Add your updated indicator to a TradingView chart 2) Add the Strategy Template as well to the SAME chart 3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator) Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember. From then, you should start seeing the signals and plenty of other stuff on your chart. 🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time II) BOT Risk Management: - Max Drawdown: Mode: Select whether the max drawdown is calculated in percentage (%) or USD. Value: If the max drawdown reaches this specified value, set a value to halt the bot. - Max Consecutive Days: Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached. - Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot. - Max Losing Streak: Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row. - Max Losing Streak Length: Set the maximum length of a losing streak allowed. Margin Call: - Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it. Margin Call (%): Set the percentage value to trigger this feature. - Close BOT Total Loss: Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached. - Total Loss ($): Set the total loss value in USD to trigger this feature. Intraday BOT Risk Management: - Intraday Losses: Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses. Mode: Select whether the intraday loss is calculated in percentage (%) or USD. - Max Intraday Losses (%): Set the value for maximum intraday losses. Limit Intraday Trades: - Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades. - Max Intraday Trades: Set the maximum number of intraday trades allowed. Restart Intraday EA: III) Order Types and Position Sizing - Choose between market or limit orders. - Set your position size directly in the template. Please use the position size from the “Inputs” and not the “Properties” tab. I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab. IV) Advanced Take-Profit and Stop-Loss Options - Choose to set your SL/TP in either USD or percentages. - Option for multiple take-profit levels and trailing stop losses. - Move your stop loss to break even +/- offset in USD for “risk-free” trades. V) Miscellaneous: Retry order openings if they fail. Order Types: Select and specify order type and price settings. Position Size: Define the type and size of positions. Leverage: Leverage settings, including margin type and hedge mode. Session: Limit trades to specific sessions. Dates: Limit trades to a specific date range. Trades Direction: Direction: Specify the market direction for opening positions. VI) Logger The TradingView.TO commands are logged in the TradingView logger. You'll find more information about it in this TradingView blog post . WHY YOU MIGHT NEED THIS TEMPLATE 1) Transform your indicator into a TradingView.TO trading bot more easily than before Connect your indicator to the template Create your alerts Set your EA settings 2) Save Time Auto-generated alert messages for TradingView.TO. I tested them all and checked with the support team what could/couldn’t be done. 3) Be in Control Manage your trading risks with advanced features. 4) Customizable Fits various trading styles and asset classes. REQUIREMENTS * Make sure you have your TradingView.TO account * If there is any issue with the template, ask me in the comments section - I’ll answer quickly. BACKTEST RESULTS FROM THIS POST 1) I connected this strategy template to a dummy Supertrend script. I could have selected any other indicator or concept for this script post. I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with TradingView.TO. 2) The backtest results aren't relevant for this educational script publication. I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :) 3) This template is made to take 1 trade per direction at any given time. Pyramiding is set to 1 on TradingView. The strategy default settings are: * Initial Capital: 100000 USD * Position Size: 1% * Commission Percent: 0.075% * Slippage: 1 tick * No margin/leverage used
Стратегия Pine Script®
от Daveatt
6
ProfitView Strategy TemplateHello traders, This script took me a full week of coding/testing, sweat, and tears - and I’m too nice as I’m giving it for free to the community. If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further. This Pine Script v5 strategy template is engineered for maximum customization and risk management. Best part? This Pine Script v5 template facilitates the dynamic construction of ProfitView alerts, sparing users the time and effort of mastering the ProfitView syntax and manually creating alert commands. This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via the ProfitView Chrome extension. IMPORTANT NOTES ProfitView is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, etc.) for automating trading. Many traders don't know how to dynamically create ProfitView-compatible alerts using the data from their TradingView scripts. Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly. This script showcases how to create ProfitView alerts dynamically. TRADINGVIEW ALERTS 1) You'll have to create one alert per asset X timeframe = 1 chart. Example: 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes) 2) Select the Order fills and alert() function calls condition 3) For each alert, the alert message is pre-configured with the text below {{strategy.order.alert_message}} Please leave it as it is. It's a TradingView native variable that will fetch the alert text messages built by the script. 4) ProfitView doesn't use webhook technology, so setting a webhook URL from the alerts notifications tab is unnecessary. KEY FEATURES I) Modular Indicator Connection * plug your existing indicator into the template. * Only two lines of code are needed for full compatibility. Step 1: Create your connector Adapt your indicator with only 2 lines of code and then connect it to this strategy template. To do so: 1) Find in your indicator where the conditions print the long/buy and short/sell signals. 2) Create an additional plot as below I'm giving an example with a Two moving averages cross. Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions. //@version=5 indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true) atrPeriod = input.int(10, "ATR Length", minval = 1) factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01) = ta.supertrend(factor, atrPeriod) supertrend := barstate.isfirst ? na : supertrend bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none) upTrend = plot(direction &lt; 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr) downTrend = plot(direction &lt; 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr) fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false) fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false) buy = ta.crossunder(direction, 0) sell = ta.crossunder(direction, 0) //////// CONNECTOR SECTION //////// Signal = buy ? 1 : sell ? -1 : 0 plot(Signal, title = "Signal", display = display.data_window) //////// CONNECTOR SECTION //////// Important Notes 🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal Now, you can connect your indicator to the Strategy Template using the method below or that one. Step 2: Connect the connector 1) Add your updated indicator to a TradingView chart 2) Add the Strategy Template as well to the SAME chart 3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator) Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember. From then, you should start seeing the signals and plenty of other stuff on your chart. 🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time II) BOT Risk Management: - Max Drawdown: Mode: Select whether the max drawdown is calculated in percentage (%) or USD. Value: If the max drawdown reaches this specified value, set a value to halt the bot. - Max Consecutive Days: Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached. - Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot. - Max Losing Streak: Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row. - Max Losing Streak Length: Set the maximum length of a losing streak allowed. Margin Call: - Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it. Margin Call (%): Set the percentage value to trigger this feature. - Close BOT Total Loss: Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached. - Total Loss ($): Set the total loss value in USD to trigger this feature. Intraday BOT Risk Management: - Intraday Losses: Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses. Mode: Select whether the intraday loss is calculated in percentage (%) or USD. - Max Intraday Losses (%): Set the value for maximum intraday losses. Limit Intraday Trades: - Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades. - Max Intraday Trades: Set the maximum number of intraday trades allowed. Restart Intraday EA: - Use Restart Intraday EA: Enable/Disable a feature to restart the bot at the first bar of the next day if it has been stopped with an intraday risk management safeguard. III) Order Types and Position Sizing - Choose between market, limit, or stop orders. - Set your position size directly in the template. Please use the position size from the “Inputs” and not the “Properties” tab. I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab. IV) Advanced Take-Profit and Stop-Loss Options - Choose to set your SL/TP in either pips or percentages. - Option for multiple take-profit levels and trailing stop losses. - Move your stop loss to break even +/- offset in pips for “risk-free” trades. V) Miscellaneous Retry order openings if they fail. Order Types: Select and specify order type and price settings. Position Size: Define the type and size of positions. Leverage: Leverage settings, including margin type and hedge mode. Session: Limit trades to specific sessions. Dates: Limit trades to a specific date range. Trades Direction: Direction: Specify the market direction for opening positions. VI) Notifications (Telegram/Discord/Email/IFTTT/Twilio/SMS) Customize notifications sent to Telegram, Discord, Email, IFTTT, Twilio, and ProfitView Logger. VII) Logger The ProfitView commands are logged in the TradingView logger. You'll find more information about it in this TradingView blog post . WHY YOU MIGHT NEED THIS TEMPLATE 1) Transform your indicator into a ProfitView trading bot more easily than before Connect your indicator to the template Create your alerts Set your EA settings 2) Save Time Auto-generated alert messages for ProfitView. I tested them all and checked with the support team what could/couldn’t be done. 3) Be in Control Manage your trading risks with advanced features. 4) Customizable Fits various trading styles and asset classes. REQUIREMENTS * Make sure you have your ProfitView account and do the settings correctly in your Chrome extension. If you don't know how to do it, read the documentation + ask for help in the ProfitView Discord support channel. * If there is any issue with the template, ask me in the comments section - I’ll answer quickly. BACKTEST RESULTS FROM THIS POST 1) I connected this strategy template to a dummy Supertrend script. I could have selected any other indicator or concept for this script post. I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with ProfitView. 2) The backtest results aren't relevant for this educational script publication. I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :) 3) This template is made to take 1 trade per direction at any given time. Pyramiding is set to 1 on TradingView. The strategy default settings are: * Initial Capital: 100000 USD * Position Size: 1% * Commission Percent: 0.075% * Slippage: 1 tick * No margin/leverage used Best regards, Dave
Стратегия Pine Script®
от Daveatt
THE TRADE MEISTER PROTOCOL - VOLUME PROFILE EDITIONTHE TRADE MEISTER PROTOCOL - VOLUME PROFILE EDITION The ATM Protocol is a regime-filtered trading framework that solves the fundamental problem causing retail trader losses: taking counter-trend signals during unfavorable market conditions. It's a unified decision-making system where trade signals must pass through multiple layers of confirmation before execution. The core innovation is the Regime Filter - a proprietary logic system that gates all trade signals through RSI momentum states AND VWAP swing structure confirmation. Signals that fire during opposing regimes are blocked and marked with an X on your chart. 1. Regime Filter System - Multi-layered confirmation logic requiring RSI momentum (threshold-optimized at 65/32) AND VWAP swing alignment before allowing UT Bot signals to execute. When conditions don't align, signals are rejected in real-time. 2. Automated Trade Setup Calculator - Proprietary algorithm that scans support/resistance structure (100/500/1000-bar lookbacks), identifies nearest structural levels for stop placement, calculates two profit targets, and displays live Risk:Reward ratios. Falls back to ATR-based calculations when structure is absent. 3. Adaptive VWAP with Volatility Adjustment - Custom implementation using alpha decay functions and ATR-based volatility ratios to adjust tracking periods dynamically. Resets on swing highs/lows rather than session anchors, rendered as polylines for clarity. Volume Profile Integration adds institutional context: Session-based profiling (Tokyo/London/NY/Daily/Weekly/Monthly/Quarterly/Yearly) with POC/VAH/VAL identification shows where institutions actually traded, not just where price went. Supports both Volume and Open Interest data types for futures traders. Longevity Zone Tracking displays support/resistance age in Days/Months/Years with automatic violation removal, helping identify which levels have institutional significance based on duration. The Problem This Solves Most traders struggle with conflicting signals. RSI says oversold, MACD shows bearish, volume is declining, VWAP is below price - which do you trust? The result: analysis paralysis or worse, taking every signal and getting chopped to pieces. The ATM Protocol's solution: Create a hierarchy where signals must satisfy multiple conditions simultaneously. The regime filter acts as the gatekeeper - no signal executes unless the market regime confirms the direction. How the Regime Filter Works The regime filter operates in three stages: Stage 1 - RSI Momentum Assessment: - RSI crossing above 65 while price shows upward EMA momentum = Bullish Regime - RSI dropping below 32 with downward price momentum = Bearish Regime - Neither condition = Neutral (no directional bias) Stage 2 - VWAP Swing Structure: - Most recent swing high > most recent swing low = VWAP Bullish - Most recent swing low > most recent swing high = VWAP Bearish - Uses 50-period swing detection (configurable) Stage 3 - Signal Filtration: - UT Bot buy signals only execute when: Bullish Regime + VWAP Bullish - UT Bot sell signals only execute when: Bearish Regime + VWAP Bearish - All other signals are rejected and marked You can disable the filter or remove VWAP requirement in settings for more aggressive trading, but the default configuration prioritizes quality over quantity. Volume Profile: Institutional Context Standard indicators show where price moved. Volume Profile shows where volume accumulated - revealing where institutions made decisions. Key Levels Explained: Point of Control (POC): The price level with the most volume during the session. Institutions traded most heavily here. Acts as magnetic support/resistance. Value Area High (VAH) / Value Area Low (VAL): The price range containing 70% of the session's volume (configurable). This is the "fair value" zone where institutions accepted prices. Trading Above VAH: Bullish - price accepted above value, new buyers stepping in Trading Below VAL: Bearish - price rejected, sellers in control Inside Value Area: Choppy - expect range-bound behavior until breakout Session Types: - Intraday (Tokyo/London/NY): See where each major forex session traded - Daily: Traditional market profile view - Weekly/Monthly: Swing traders, identify major accumulation zones - Quarterly/Yearly: Position traders, institutional long-term levels The Volume Profile uses intra-bar data for precision and supports Open Interest for futures markets, showing delta OI changes that reveal institutional positioning in derivatives. Automated Trade Setup Calculator This is where theory becomes execution. When the regime filter confirms a setup, the calculator automatically: For Long Setups: 1. Scans support levels (100, 500, 1000-bar lows) 2. Places stop at nearest support below current price 3. Identifies next two resistance levels above for targets 4. Calculates R:R ratio (Target 1 distance / Stop distance) 5. Displays all values in the dashboard in real-time For Short Setups: 1. Scans resistance levels (100, 500, 1000-bar highs) 2. Places stop at nearest resistance above current price 3. Identifies next two support levels below for targets 4. Calculates R:R ratio 5. Updates live as price moves Fallback Logic: If no structural levels exist nearby (new market, post-gap), the calculator uses ATR-based placement: - Stop: 1.5 x ATR from entry - Target 1: 2.0 x ATR from entry - Target 2: 4.0 x ATR from entry This removes the 15-20 minutes traders typically spend manually measuring setups. The math happens instantly. Dashboard Intelligence The dashboard provides command-center visibility: Position State: Long/Short/Flat with UT Bot status Regime Status: Locked (filter active) or Unlocked, showing current bias VWAP Swing: Current swing structure (Bullish/Bearish) Multi-Timeframe Matrix: 9 timeframes showing EMA trend alignment (1M to 1Month) Market Data: Volume analysis, MACD, Stochastic, ATR state AI Predictive: Synthesized trend bias using smoothed RSI + momentum Trade Setup: Live entry, two targets, stop loss, R:R ratio All information updates tick-by-tick. One glance tells you: Is there a setup? What's the regime? Where are my levels? How to Use This Protocol Philosophy: You Are the Sniper, This Is Your Scope The ATM Protocol doesn't predict the future. It analyzes current structure and tells you when conditions favor high-probability setups. You decide when to pull the trigger. Step-by-Step Workflow: 1. Check Regime (Dashboard Top Section) Look for: - 🔒LONG = Bullish regime confirmed, look for longs only - 🔒SHORT = Bearish regime confirmed, look for shorts only - ⚪NEUTRAL = No regime, stay flat or reduce size 2. Wait for UT Signal - Green "Buy" label = Long signal (only appears during bullish regime) - Red "Sell" label = Short signal (only appears during bearish regime) - Gray X = Rejected signal (counter-trend attempt blocked by filter) 3. Confirm with Volume Profile Ideal long setup: - Price at or near VAL (value area low) - Buy signal fires - Regime is bullish - POC is above current price (room to move) Ideal short setup: - Price at or near VAH (value area high) - Sell signal fires - Regime is bearish - POC is below current price (room to fall) 4. Review Trade Setup (Dashboard AI Section) Check: - Entry: Current price - Target 1: First profit objective - Target 2: Full profit objective - Stop Loss: Invalidation level - R:R: Aim for minimum 1.5:1, preferably 2:1+ 5. Execute and Manage - Enter at current price when all conditions align - Set stop at displayed level - Take partial profits at Target 1 (50% position) - Hold remaining for Target 2 or trail with LinReg candles - Exit immediately if regime flips (dashboard shows change) Position Management with LinReg: The script plots linear regression candles colored by position state: - Green candles = In long position - Red candles = In short position - Blue signal line = Dynamic trend Use these to trail stops or add to winners during strong trends. Longevity Zones: Time-Tested Levels Support and resistance zones that have held for extended periods carry more weight. The longevity tracker shows: - Zone age: Days, Months, or Years - Bar count: Total bars since zone formation - Auto-deletion: Zones disappear when price violates them Why This Matters: A resistance zone that has held for 6 months indicates institutional interest. A support zone that formed yesterday is untested. Longevity helps you prioritize which levels matter most. Zones display as semi-transparent rectangles (red for resistance, green for support) with labels showing duration. Place stops beyond these zones for optimal invalidation points. What This Tool Does NOT Do Brutal Honesty Section: ❌ Does NOT predict the future - Past results never guarantee future performance. Markets change. Regimes shift. Volatility spikes. Nothing is certain. ❌ Does NOT work in all conditions - Ranging, low-volatility, or news-driven markets produce fewer quality setups. You'll have periods with no signals. This is intentional - we're filtering for quality. ❌ Does NOT eliminate losses - Even 3:1 R:R setups fail. Stops get hit. The goal is positive expectancy over 50+ trades, not winning every single one. ❌ Does NOT replace risk management - If you risk 10% per trade, you'll blow your account regardless of how good the tool is. Proper position sizing is YOUR responsibility. ❌ Does NOT guarantee profits - Anyone claiming otherwise is lying. Trading is probabilistic. This tool identifies favorable probabilities. Execution and discipline are on you. What It Requires From You: ✅ Learning curve - 2-4 weeks to understand regime changes, volume profile context, and setup identification. This isn't "add indicator, print money." ✅ Discipline - Following regime filter means accepting fewer trades. If you force trades during neutral regimes, the tool can't help you. ✅ Risk management - Position sizing, stop losses, profit taking - these are ALWAYS your decisions. The calculator suggests levels. You execute. ✅ Psychological control - Rejected signals (gray X) protect you. Don't override them emotionally. Trust the process over dozens of trades, not individual setups. Technical Specifications Components: - UT Bot (ATR-based trailing stop signals) - Public domain base, regime-filtered - RSI (14-period default) - Momentum regime definition with optimized thresholds - Adaptive VWAP - Custom volatility-adjusted implementation with swing resets - Volume Profile - Session-based institutional level detection (8 session types) - Linear Regression - Position state visualization with smoothing - Fibonacci Bands - ATR or StdDev based volatility bands - Support/Resistance - Multi-timeframe structural levels (100/500/1000 bars) - Longevity Zones - Duration-tracked pivot-based S/R Regime Filter Logic: - Bullish = RSI > 65 AND VWAP Swing Bullish (optional) - Bearish = RSI < 32 AND VWAP Swing Bearish (optional) - Neutral = Neither condition met - Configurable: Disable filter or remove VWAP requirement Volume Profile Settings: - Session Types: Tokyo/London/NY/Daily/Weekly/Monthly/Quarterly/Yearly - Resolution: 5-100 rows (higher = more detail) - Value Area: 60-80% configurable (default 70%) - Data Types: Volume or Open Interest (futures) - Display Modes: 3 visual styles The ATM Protocol is a scope, not autopilot. It identifies high-probability setups when conditions align. The discipline to wait for confirmation, the courage to execute when signals fire, and the wisdom to honor stops - these come from you. **Trading is hard.** Most retail traders lose because they take every signal, fight trends, or revenge trade after losses. This tool can't fix those problems. What it CAN do is show you when the market structure favors your direction and automatically calculate logical trade parameters. **Use it as designed:** - Trust the regime filter (let it block counter-trend trades) - Respect the setup calculator (stops exist for a reason) - Understand Volume Profile context (trade with institutions, not against them) - Give it time (evaluate over 50+ trades minimum) The goal isn't to win every trade. It's to create positive expectancy through better trade selection and execution. The regime filter handles selection. You handle execution. Good hunting. 🎯 --- **Disclaimer:** This indicator is a tool for technical analysis and does not constitute financial advice. Trading carries significant risk of capital loss. Past performance of any trading methodology does not guarantee future results. The creator assumes no responsibility for trading outcomes. Users must develop their own trading plan, risk management system, and execution discipline. Never risk more than you can afford to lose.
Индикатор Pine Script®
от absolutedollar
Quantum Reversal Engine [ApexLegion]Quantum Reversal Engine STRATEGY OVERVIEW This strategy is constructed using 5 custom analytical filters that analyze different market dimensions - trend structure, momentum expansion, volume confirmation, price action patterns, and reversal detection - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions. Why These Custom Filters Were Independently Developed: This strategy employs five custom-developed analytical filters: 1. Apex Momentum Core (AMC) - Custom oscillator with volatility-scaled deviation calculation Standard oscillators lag momentum shifts by 2-3 bars. Custom calculation designed for momentum analysis 2. Apex Wick Trap (AWT) - Wick dominance analysis for trap detection Existing wick analysis tools don't quantify trap conditions. Uses specific ratios for wick dominance detection 3. Apex Volume Pulse (AVP) - Volume surge validation with participation confirmation Volume indicators typically use simple averages. Uses surge multipliers with participation validation 4. Apex TrendGuard (ATG) - Angle-based trend detection with volatility band integration EMA slope calculations often produce false signals. Uses angle analysis with volatility bands for confirmation 5. Quantum Composite Filter (QCF) - Multi-component scoring and signal generation system Composite scoring designed to filter noise by requiring multiple confirmations before signal activation. Each filter represents mathematical calculations designed to address specific analytical requirements. Framework Operation: The strategy functions as a scoring framework where each filter contributes weighted points based on market conditions. Entry signals are generated when minimum threshold scores are met. Exit management operates through a three-tier system with continued signal strength evaluation determining position holds versus closures at each TP level. Integration Challenge: The core difficulty was creating a scoring system where five independent filters could work together without generating conflicting signals. This required backtesting to determine effective weight distributions. Custom Filter Development: Each of the five filters represents analytical approaches developed through testing and validation: Integration Validation: Each filter underwent individual testing before integration. The composite scoring system required validation to verify that filters complement rather than conflict with each other, resulting in a cohesive analytical framework that was tested during the development period. These filters represent custom-developed components created specifically for this strategy, with each component addressing different analytical requirements through testing and parameter adjustment. Programming Features: Multi-timeframe data handling with backup systems Performance optimization techniques Error handling for live trading scenarios Parameter adaptation based on market conditions Strategy Features: Uses multi-filter confirmation approach Adapts position holding based on continued signal strength Includes analysis tools for trade review and optimization Ongoing Development: The strategy was developed through testing and validation processes during the creation period. COMPONENT EXPLANATION EMA System Uses 8 exponential moving averages (7, 14, 21, 30, 50, 90, 120, 200 periods) for trend identification. Primary signals come from 8/21 EMA crossovers, while longer EMAs provide structural context. EMA 1-4 determine short-term structure, EMA 5-8 provide long-term trend confirmation. Apex Momentum Core (AMC) Built custom oscillator mathematics after testing dozens of momentum calculation methods. Final algorithm uses price deviation from EMA baseline with volatility scaling to reduce lag while maintaining accuracy across different market conditions. Custom momentum oscillator using price deviation from EMA baseline: apxCI = 100 * (source - emaBase) / (sensitivity * sqrt(deviation + 1)) fastLine = EMA(apxCI, smoothing) signalLine = SMA(fastLine, 4) Signals generate when fastLine crosses signalLine at +50/-50 thresholds. This identifies momentum expansion before traditional oscillators. Apex Volume Pulse (AVP) Created volume surge analysis that goes beyond simple averages. Extensive testing determined 1.3x multiplier with participation validation provides reliable confirmation while filtering false volume spikes. Compares current volume to 21-period moving average. Requires 1.3x average volume for signal confirmation. This filters out low-volume moves during quiet periods and confirms breakouts with actual participation. Apex Wick Trap (AWT) Developed proprietary wick trap detection through analysis of failed breakout patterns. Tested various ratio combinations before settling on 60% wick dominance + 20% body limit as effective trap identification parameters. Analyzes candle structure to identify failed breakouts: candleRange = math.max(high - low, 0.00001) candleBody = math.abs(close - open) bodyRatio = candleBody / candleRange upperWick = high - math.max(open, close) lowerWick = math.min(open, close) - low upperWickRatio = upperWick / candleRange lowerWickRatio = lowerWick / candleRange trapWickLong = showAWT and lowerWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close > open trapWickShort = showAWT and upperWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close < open This catches reversals after fake breakouts. Apex TrendGuard (ATG) Built angle-based trend detection after standard EMA crossovers proved insufficient. Combined slope analysis with volatility bands through iterative testing to eliminate false trend signals. EMA slope analysis with volatility bands: Fast EMA (21) vs Slow EMA (55) for trend direction Angle calculation: atan(fast - slow) * 180 / π ATR bands (1.75x multiplier) for breakout confirmation Minimum 25° angle for strong trend classification Core Algorithm Framework 1. Composite Signal Generation calculateCompositeSignals() => // Component Conditions structSignalLong = trapWickLong structSignalShort = trapWickShort momentumLong = amcBuySignal momentumShort = amcSellSignal volumeSpike = volume > volAvg_AVP * volMult_AVP priceStrength_Long = close > open and close > close priceStrength_Short = close < open and close < close rsiMfiComboValue = (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2 reversalTrigger_Long = ta.crossover(rsiMfiComboValue, 50) reversalTrigger_Short = ta.crossunder(rsiMfiComboValue, 50) isEMACrossUp = ta.crossover(emaFast_ATG, emaSlow_ATG) isEMACrossDown = ta.crossunder(emaFast_ATG, emaSlow_ATG) // Enhanced Composite Score Calculation scoreBuy = 0.0 scoreBuy += structSignalLong ? scoreStruct : 0.0 scoreBuy += momentumLong ? scoreMomentum : 0.0 scoreBuy += flashSignal ? weightFlash : 0.0 scoreBuy += blinkSignal ? weightBlink : 0.0 scoreBuy += volumeSpike_AVP ? scoreVolume : 0.0 scoreBuy += priceStrength_Long ? scorePriceAction : 0.0 scoreBuy += reversalTrigger_Long ? scoreReversal : 0.0 scoreBuy += emaAlignment_Bull ? weightTrendAlign : 0.0 scoreBuy += strongUpTrend ? weightTrendAlign : 0.0 scoreBuy += highRisk_Long ? -1.2 : 0.0 scoreBuy += signalGreenDot ? 1.0 : 0.0 scoreBuy += isAMCUp ? 0.8 : 0.0 scoreBuy += isVssBuy ? 1.5 : 0.0 scoreBuy += isEMACrossUp ? 1.0 : 0.0 scoreBuy += signalRedX ? -1.0 : 0.0 scoreSell = 0.0 scoreSell += structSignalShort ? scoreStruct : 0.0 scoreSell += momentumShort ? scoreMomentum : 0.0 scoreSell += flashSignal ? weightFlash : 0.0 scoreSell += blinkSignal ? weightBlink : 0.0 scoreSell += volumeSpike_AVP ? scoreVolume : 0.0 scoreSell += priceStrength_Short ? scorePriceAction : 0.0 scoreSell += reversalTrigger_Short ? scoreReversal : 0.0 scoreSell += emaAlignment_Bear ? weightTrendAlign : 0.0 scoreSell += strongDownTrend ? weightTrendAlign : 0.0 scoreSell += highRisk_Short ? -1.2 : 0.0 scoreSell += signalRedX ? 1.0 : 0.0 scoreSell += isAMCDown ? 0.8 : 0.0 scoreSell += isVssSell ? 1.5 : 0.0 scoreSell += isEMACrossDown ? 1.0 : 0.0 scoreSell += signalGreenDot ? -1.0 : 0.0 compositeBuySignal = enableComposite and scoreBuy >= thresholdCompositeBuy compositeSellSignal = enableComposite and scoreSell >= thresholdCompositeSell if compositeBuySignal and compositeSellSignal compositeBuySignal := false compositeSellSignal := false = calculateCompositeSignals() // Final Entry Signals entryCompositeBuySignal = compositeBuySignal and ta.rising(emaFast_ATG, 2) entryCompositeSellSignal = compositeSellSignal and ta.falling(emaFast_ATG, 2) Calculates weighted scores from independent modules and activates signals only when threshold requirements are met. 2. Smart Exit Hold Evaluation System evaluateSmartHold() => compositeBuyRecentCount = 0 compositeSellRecentCount = 0 for i = 0 to signalLookbackBars - 1 compositeBuyRecentCount += compositeBuySignal ? 1 : 0 compositeSellRecentCount += compositeSellSignal ? 1 : 0 avgVolume = ta.sma(volume, 20) volumeSpike = volume > avgVolume * volMultiplier // MTF Bull/Bear conditions mtf_bull = mtf_emaFast_final > mtf_emaSlow_final mtf_bear = mtf_emaFast_final < mtf_emaSlow_final emaBackupDivergence = math.abs(mtf_emaFast_backup - mtf_emaSlow_backup) / mtf_emaSlow_backup emaBackupStrong = emaBackupDivergence > 0.008 mtfConflict_Long = inLong and mtf_bear and emaBackupStrong mtfConflict_Short = inShort and mtf_bull and emaBackupStrong // Layer 1: ATR-Based Dynamic Threshold (Market Volatility Intelligence) atr_raw = ta.atr(atrLen) atrValue = na(atr_raw) ? close * 0.02 : atr_raw atrRatio = atrValue / close dynamicThreshold = atrRatio > 0.02 ? 1.0 : (atrRatio > 0.01 ? 1.5 : 2.8) // Layer 2: ROI-Conditional Time Intelligence (Selective Pressure) timeMultiplier_Long = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure holdTimer_Long <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base holdTimer_Long <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter 1.3 // Loss positions 17+ bars: +30% stricter timeMultiplier_Short = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure holdTimer_Short <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base holdTimer_Short <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter 1.3 // Loss positions 17+ bars: +30% stricter // Dual-Layer Threshold Calculation baseThreshold_Long = mtfConflict_Long ? dynamicThreshold + 1.0 : dynamicThreshold baseThreshold_Short = mtfConflict_Short ? dynamicThreshold + 1.0 : dynamicThreshold timeAdjustedThreshold_Long = baseThreshold_Long * timeMultiplier_Long timeAdjustedThreshold_Short = baseThreshold_Short * timeMultiplier_Short // Final Smart Hold Decision with Dual-Layer Intelligence smartHold_Long = not mtfConflict_Long and smartScoreLong >= timeAdjustedThreshold_Long and compositeBuyRecentCount >= signalMinCount smartHold_Short = not mtfConflict_Short and smartScoreShort >= timeAdjustedThreshold_Short and compositeSellRecentCount >= signalMinCount = evaluateSmartHold() Evaluates whether to hold positions past TP1/TP2/TP3 levels based on continued signal strength, volume confirmation, and multi-timeframe trend alignment HOW TO USE THE STRATEGY Step 1: Initial Setup Apply strategy to your preferred timeframe (backtested on 15M) Enable "Use Heikin-Ashi Base" for smoother signals in volatile markets "Show EMA Lines" and "Show Ichimoku Cloud" are enabled for visual context Set default quantities to match your risk management (5% equity default) Step 2: Signal Recognition Visual Signal Guide: Visual Signal Guide - Complete Reference: 🔶 Red Diamond: Bearish momentum breakdown - short reversal signal 🔷 Blue Diamond: Strong bullish momentum - long reversal signal 🔵 Blue Dot: Volume-confirmed directional move - trend continuation 🟢 Green Dot: Bullish EMA crossover - trend reversal confirmation 🟠 Orange X: Oversold reversal setup - counter-trend opportunity ❌ Red X: Bearish EMA breakdown - trend reversal warning ✡ Star Uprising: Strong bullish convergence 💥 Ultra Entry: Ultra-rapid downward momentum acceleration ▲ VSS Long: Velocity-based bullish momentum confirmation ▼ VSS Short: Velocity-based bearish momentum confirmation Step 3: Entry Execution For Long Positions: 1. ✅ EMA1 crossed above EMA2 exactly 3 bars ago [ta.crossover(ema1,ema2) ] 2. ✅ Current EMA structure: EMA1 > EMA2 (maintained) 3. ✅ Composite score ≥ 5.0 points (6.5+ for 5-minute timeframes) 4. ✅ Cooldown period completed (no recent stop losses) 5. ✅ Volume spike confirmation (green dot/blue dot signals) 6. ✅ Bullish candle closes above EMA structure For Short Positions: 1. ✅ EMA1 crossed below EMA2 exactly 3 bars ago [ta.crossunder(ema1,ema2) ] 2. ✅ Current EMA structure: EMA1 < EMA2 (maintained) 3. ✅ Composite score ≥ 5.4 points (7.0+ for 5-minute timeframes) 4. ✅ Cooldown period completed (no recent stop losses) 5. ✅ Momentum breakdown (red diamond/red X signals) 6. ✅ Bearish candle closes below EMA structure 🎯 Critical Timing Note: The strategy requires EMA crossover to have occurred 3 bars prior to entry, not at the current bar. This attempts to avoid premature entries and may improve signal reliability. Step 4: Reading Market Context EMA Ribbon Interpretation: All EMAs ascending = Strong uptrend context EMAs 1-3 above EMAs 4-8 = Bullish structure Tight EMA spacing = Low volatility/consolidation Wide EMA spacing = High volatility/trending Ichimoku Cloud Context: Price above cloud = Bullish environment Price below cloud = Bearish environment Cloud color intensity = Momentum strength Thick cloud = Strong support/resistance THE SMART EXIT GRID SYSTEM Smart Exit Grid Approach: The Smart Exit Grid uses dynamic hold evaluation that continuously analyzes market conditions after position entry. This differs from traditional fixed profit targets by adapting exit timing based on real-time signal strength. How Smart Exit Grid System Works The system operates through three evaluation phases: Smart Score Calculation: The smart score calculation aggregates 22 signal components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. MTF analysis provides additional confirmation as a separate validation layer. Signal Stack Management: The per-tick signal accumulation system monitors 22 active signal types with MTF providing trend validation and conflict detection as a separate confirmation layer. Take Profit Progression: Smart Exit Activation: The QRE system activates Smart Exit Grid immediately upon position entry. When strategy.entry() executes, the system initializes monitoring systems designed to track position progress. Upon position opening, holdTimer begins counting, establishing the foundation for subsequent decisions. The Smart Exit Grid starts accumulating signals from entry, with all 22 signal components beginning real-time tracking when the trade opens. The system operates on continuous evaluation where smartScoreLong and smartScoreShort calculate from the first tick after entry. QRE's approach is designed to capture market structure changes, trend deteriorations, or signal pattern shifts that can trigger protective exits even before the first take profit level is reached. This activation creates a proactive position management framework. The 8-candle sliding window starts from entry, meaning that if market conditions change rapidly after entry - due to news events, liquidity shifts, or technical changes - the system can respond within the configured lookback period. TP Markers as Reference Points: The TP1, TP2, and TP3 levels function as reference points rather than mandatory exit triggers. When longTP1Hit or shortTP1Hit conditions activate, they serve as profit confirmation markers that inform the Smart Exit algorithm about achieved reward levels, but don't automatically initiate position closure. These TP markers enhance the Smart Exit decision matrix by providing profit context to ongoing signal evaluation. The system recognizes when positions have achieved target returns, but the actual exit decision remains governed by continuous smart score evaluation and signal stack analysis. TP2 Reached: Enhanced Monitoring TP2 represents significant profit capture with additional monitoring features: This approach is designed to help avoid premature profit-taking during trending conditions. If TP2 is reached but smartScoreLong remains above the dynamic threshold and the 8-candle sliding window shows persistent signals, the position continues holding. If market structure deteriorates before reaching TP2, the Smart Exit can trigger closure based on signal analysis. The visual TP circles that appear when levels are reached serve as performance tracking tools, allowing users to see how frequently entries achieve various profit levels while understanding that actual exit timing depends on market structure analysis. Risk Management Systems: Operating independently from the Smart Exit Grid are two risk management systems: the Trap Wick Detection Protocol and the Stop Loss Mechanism. These systems maintain override authority over other exit logic. The Trap Wick System monitors for conditionBearTrapExit during long positions and conditionBullTrapExit during short positions. When detected, these conditions trigger position closure with state reset, bypassing Smart Exit evaluations. This system recognizes that certain candlestick patterns may indicate reversal risk. Volatility Exit Monitoring: The strategy monitors for isStrongBearCandle combined with conditionBearTrapExit, recognizing when market structure may be shifting. Volume Validation: Before exiting on volatility, the strategy requires volume confirmation: volume > ta.sma(volume, 20) * 1.8. This is designed to filter exits on weak, low-volume movements. The Stop Loss Mechanism operates through multiple triggers including traditional price-based stops (longSLHit, shortSLHit) and early exit conditions based on smart score deterioration combined with negative ROI. The early exit logic activates when smartScoreLong < 1.0 or smartScoreShort < 1.0 while realROI < -0.9%. These risk management systems are designed so that risk scenarios can trigger protective closure with state reset across all 22 signal counters, TP tracking variables, and smart exit states. This architecture - Smart Exit activation, TP markers as navigation tools, and independent risk management - creates a position management system that adapts to market conditions while maintaining risk discipline through dedicated protection protocols. TP3 Reached: Enhanced Protection Once TP3 is hit, the strategy shifts into enhanced monitoring: EMA Structure Monitoring: isEMAStructureDown becomes a primary exit trigger MTF Alignment: The higher timeframe receives increased consideration Wick Trap Priority: conditionBearTrapExit becomes an immediate exit signal Approach Differences: Traditional Fixed Exits: Exit at predetermined levels regardless of market conditions May exit during trend continuation May exit before trend completion Limited adaptation to changing volatility Smart Exit Grid Approach: Adaptive timing based on signal conditions Exits when supporting signals weaken Multi-timeframe validation for trend confirmation Volume confirmation requirements for holds Structural monitoring for trend analysis Dynamic ATR-Based Smart Score Threshold System Market Volatility Adaptive Scoring // Real-time ATR Analysis atr_raw = ta.atr(atrLen) atrValue = na(atr_raw) ? close * 0.02 : atr_raw atrRatio = atrValue / close // Three-Tier Dynamic Threshold Matrix dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold (atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard 2.8) // Low volatility: Higher threshold The market volatility adaptive scoring calculates real-time ATR with a 2% fallback for new markets. The atrRatio represents the relationship between current volatility and price, creating a foundation for threshold adjustment. The three-tier dynamic threshold matrix responds to market conditions by adjusting requirements based on volatility levels: lowering thresholds during high volatility periods above 2% ATR ratio to 1.0 points, maintaining standard requirements at 1.5 points for medium volatility between 1-2%, and raising standards to 2.8 points during low volatility periods below 1%. Profit-Loss Adaptive Management: The system applies different evaluation criteria based on position performance: Winning Positions (realROI ≥ 0%): → timeMultiplier = 1.0 (No additional pressure) → Maintains base threshold requirements → Allows natural progression to TP2/TP3 levels Losing Positions (realROI < 0%): → Progressive time pressure activated → Increasingly strict requirements over time → Faster decision-making on underperforming trades ROI-Adaptive Smart Hold Decision Process: The strategy uses a profit-loss adaptive system: Winning Position Management (ROI ≥ 0%): ✅ Standard threshold requirements maintained ✅ No additional time-based pressure applied ✅ Allows positions to progress toward TP2/TP3 levels ✅ timeMultiplier remains at 1.0 regardless of hold duration Losing Position Management (ROI < 0%): ⚠️ Time-based threshold adjustments activated ⚠️ Progressive increase in required signal strength over time ⚠️ Earlier exit evaluation on underperforming positions ⚠️ timeMultiplier increases from 1.0 → 1.1 → 1.3 based on hold duration Real-Time Monitoring: Monitor Analysis Table → "Smart" filter → "Score" vs "Dynamic Threshold" Winning positions: Evaluation based on signal strength deterioration only Losing positions: Evaluation considers both signal strength and progressive time adjustments Breakeven positions (0% ROI): Treated as winning positions - no time adjustments This approach differentiates between winning and losing positions in the hold evaluation process, requiring higher signal thresholds for extended holding of losing positions while maintaining standard requirements for winning ones. ROI-Conditional Decision Matrix Examples: Scenario 1 - Winning Position in Any Market: Position ROI: +0.8% → timeMultiplier = 1.0 (regardless of hold time) ATR Medium (1.2%) → dynamicThreshold = 1.5 Final Threshold = 1.5 × 1.0 = 1.5 points ✅ Position continues Scenario 2 - Losing Position, Extended Hold: Position ROI: -0.5% → Time pressure activated Hold Time: 20 bars → timeMultiplier = 1.3 ATR Low (0.8%) → dynamicThreshold = 2.8 Final Threshold = 2.8 × 1.3 = 3.64 points ⚡ Enhanced requirements Scenario 3 - Fresh Losing Position: Position ROI: -0.3% → Time pressure activated Hold Time: 5 bars → timeMultiplier = 1.0 (still early) ATR High (2.1%) → dynamicThreshold = 1.0 Final Threshold = 1.0 × 1.0 = 1.0 points 📊 Recovery opportunity Scenario 4 - Breakeven Position: Position ROI: 0.0% → timeMultiplier = 1.0 (no pressure) Hold Time: 15 bars → No time penalty applied Final Threshold = dynamicThreshold only ⚖️ Neutral treatment 🔄8-Candle Sliding Window Signal Rotation System Composite Signal Counting Mechanism // Dynamic Lookback Window (configurable: default 8) signalLookbackBars = input.int(8, "Composite Lookback Bars", minval=1, maxval=50) // Rolling Signal Analysis compositeBuyRecentCount = 0 compositeSellRecentCount = 0 for i = 0 to signalLookbackBars - 1 compositeBuyRecentCount += compositeBuySignal ? 1 : 0 compositeSellRecentCount += compositeSellSignal ? 1 : 0 Candle Flow Example (8-bar window): → ✓ ✓ ✗ ✓ ✗ ✓ ✗ ✓ 🗑️ New Signal Count = 5/8 signals in window Threshold Check: 5 ≥ signalMinCount (2) = HOLD CONFIRMED Signal Decay & Refresh Mechanism // Signal Persistence Tracking if compositeBuyRecentCount >= signalMinCount smartHold_Long = true else smartHold_Long = false The composite signal counting operates through a configurable sliding window. The system maintains rolling counters that scan backward through the specified number of candles. During each evaluation cycle, the algorithm iterates through historical bars, incrementing counters when composite signals are detected. This creates a dynamic signal persistence measurement where recent signal density determines holding decisions. The sliding window rotation functions like a moving conveyor belt where new signals enter while the oldest signals drop off. For example, in an 8-bar window, if 5 out of 8 recent candles showed composite buy signals, and the minimum required count is 2, the system confirms the hold condition. As new bars form, the window slides forward, potentially changing the signal count and triggering exit conditions when signal density falls below the threshold. Signal decay and refresh occur continuously where smartHold_Long remains true only when compositeBuyRecentCount exceeds signalMinCount. When recent signal density drops below the minimum requirement, the system switches to exit mode. Advanced Signal Stack Management - 22-Signal Real-Time Evaluation // Long Position Signal Stacking (calc_on_every_tick=true) if inLong // Primary Reversal Signals if signalRedDiamond: signalCountRedDiamond += 1 // -0.5 points if signalStarUprising: signalCountStarUprising += 1 // +1.5 points if entryUltraShort: signalCountUltra += 1 // -1.0 points // Trend Confirmation Signals if strongUpTrend: trendUpCount_Long += 1 // +1.5 points if emaAlignment_Bull: bullAlignCount_Long += 1 // +1.0 points // Risk Assessment Signals if highRisk_Long: riskCount_Long += 1 // -1.5 points if topZone: tzoneCount_Long += 1 // -0.5 points The per-tick signal accumulation system operates with calc_on_every_tick=true for real-time responsiveness. During long positions, the system monitors primary reversal signals where Red Diamond signals subtract 0.5 points as reversal warnings, Star Uprising adds 1.5 points for continuation signals, and Ultra Short signals deduct 1.0 points as counter-trend warnings. Trend confirmation signals provide weighted scoring where strongUpTrend adds 1.5 points for aligned momentum, emaAlignment_Bull contributes 1.0 point for structural support, and various EMA-based confirmations contribute to the overall score. Risk assessment signals apply negative weighting where highRisk_Long situations subtract 1.5 points, topZone conditions deduct 0.5 points, and other risk factors create defensive scoring adjustments. The smart score calculation aggregates all 22 components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. This score updates continuously, providing the foundation for hold-or-exit decisions. MULTI-TIMEFRAME (MTF) SYSTEM MTF Data Collection The strategy requests higher timeframe data (default 30-minute) for trend confirmation: = request.security(syminfo.tickerid, mtfTimeframe, , lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_off) MTF Watchtower System - Implementation Logic The system employs a timeframe discrimination protocol where currentTFInMinutes is compared against a 30-minute threshold. This creates different operational behavior between timeframes: 📊 Timeframe Testing Results: 30M+ charts: Full MTF confirmation → Tested with full features 15M charts: Local EMA + adjusted parameters → Standard testing baseline 5M charts: Local EMA only → Requires parameter adjustment 1M charts: High noise → Limited testing conducted When the chart timeframe is 30 minutes or above, the strategy activates useMTF = true and requests external MTF data through request.security(). For timeframes below 30 minutes, including your 5-minute setup, the system deliberately uses local EMA calculations to avoid MTF lag and data inconsistencies. The triple-layer data sourcing architecture works as follows: timeframes from 1 minute to 29 minutes rely on chart-based EMA calculations for immediate responsiveness. Timeframes of 30 minutes and above utilize MTF data through the security function, with a backup system that doubles the EMA length (emaLen * 2) if MTF data fails. When MTF data is unavailable or invalid, the system falls back to local EMA as the final safety net. Data validation occurs through a pipeline where mtf_dataValid checks not only for non-null values but also verifies that EMA values are positive above zero. The system tracks data sources through mtf_dataSource which displays "MTF Data" for successful external requests, "Backup EMA" for failed MTF with backup system active, or "Chart EMA" for local calculations. 🔄 MTF Smart Score Caching & Recheck System // Cache Update Decision Logic mtfSmartIntervalSec = input.int(300, "Smart Grid Recheck Interval (sec)") // 5-minute cache canRecheckSmartScore = na(timenow) ? false : (na(lastCheckTime) or (timenow - lastCheckTime) > mtfSmartIntervalSec * 1000) // Cache Management if canRecheckSmartScore lastCheckTime := timenow cachedSmartScoreLong := smartScoreLong // Store current calculation cachedSmartScoreShort := smartScoreShort The performance-optimized caching system addresses the computational intensity of continuous MTF analysis through intelligent interval management. The mtfSmartIntervalSec parameter, defaulting to 300 seconds (5 minutes), determines cache refresh frequency. The system evaluates canRecheckSmartScore by comparing current time against lastCheckTime plus the configured interval. When cache updates trigger, the system stores current calculations in cachedSmartScoreLong and cachedSmartScoreShort, creating stable reference points that reduce excessive MTF requests. This cache management balances computational efficiency with analytical accuracy. The cache versus real-time hybrid system creates a multi-layered decision matrix where immediate signals update every tick for responsive market reaction, cached MTF scores refresh every 5 minutes for stability filtering, dynamic thresholds recalculate every bar for volatility adaptation, and sliding window analysis updates every bar for trend persistence validation. This architecture balances real-time signal detection with multi-timeframe strategic validation, creating adaptive trading intelligence that responds immediately to market changes while maintaining strategic stability through cached analysis and volatility-adjusted decision thresholds. ⚡The Execution Section Deep Dive The execution section represents the culmination of all previous systems – where analysis transforms into action. 🚪 Entry Execution: The Gateway Protocol Primary Entry Validation: Entry isn't just about seeing a signal – it's about passing through multiple security checkpoints, each designed to filter out low-quality opportunities. Stage 1: Signal Confirmation entryCompositeBuySignal must be TRUE for longs entryCompositeSellSignal must be TRUE for shorts Stage 2: Enhanced Entry Validation The strategy employs an "OR" logic system that recognizes different types of market opportunities: Path A - Trend Reversal Entry: When emaTrendReversal_Long triggers, it indicates the market structure is shifting in favor of the trade direction. This isn't just about a single EMA crossing – it represents a change in market momentum that experienced traders recognize as potential high-probability setups. Path B - Momentum Breakout Entry: The strongBullMomentum condition is where QRE identifies accelerating market conditions: Criteria: EMA1 rising for 3+ candles AND EMA2 rising for 2+ candles AND Close > 10-period high This combination captures those explosive moves where the market doesn't just trend – it accelerates, creating momentum-driven opportunities. Path C - Recovery Entry: When previous exit states are clean (no recent stop losses), the strategy permits entry based purely on signal strength. This pathway is designed to help avoid the strategy becoming overly cautious after successful trades. 🛡️ The Priority Exit Matrix: When Rules Collide Not all exit signals are created equal. QRE uses a strict hierarchy that is designed to avoid conflicting signals from causing hesitation: Priority Level 1 - Exception Exits (Immediate Action): Condition: TP3 reached AND Wick Trap detected Action: Immediate exit regardless of other signals Rationale: Historical analysis suggests wick traps at TP3 may indicate potential reversals Priority Level 2 - Structural Breakdown: Condition: TP3 active AND EMA structure deteriorating AND Smart Score insufficient Logic: isEMAStructureDown AND NOT smartHold_Long This represents the strategy recognizing that the underlying market structure that justified the trade is failing. It's like a building inspector identifying structural issues – you don't wait for additional confirmation. Priority Level 3 - Enhanced Volatility Exits: Conditions: TP2 active AND Strong counter-candle AND Wick trap AND Volume spike Logic: Multiple confirmation required to reduce false exits Priority Level 4 - Standard Smart Score Exits: Condition: Any TP level active AND smartHold evaluates to FALSE This is the bread-and-butter exit logic where signal deterioration triggers exit ⚖️ Stop Loss Management: Risk Control Protocol Dual Stop Loss System: QRE provides two stop loss modes that users can select based on their preference: Fixed Mode (Default - useAdaptiveSL = false): Uses predetermined percentage levels regardless of market volatility: - Long SL = entryPrice × (1 - fixedRiskP - slipBuffer) - Short SL = entryPrice × (1 + fixedRiskP + slipBuffer) - Default: 0.6% risk + 0.3% slippage buffer = 0.9% total stop - Consistent and predictable stop loss levels - Recommended for users who prefer stable risk parameters Adaptive Mode (Optional - useAdaptiveSL = true): Dynamic system that adjusts stop loss based on market volatility: - Base Calculation uses ATR (Average True Range) - Long SL = entryPrice × (1 - (ATR × atrMultSL) / entryPrice - slipBuffer) - Short SL = entryPrice × (1 + (ATR × atrMultSL) / entryPrice + slipBuffer) - Automatically widens stops during high volatility periods - Tightens stops during low volatility periods - Advanced users can enable for volatility-adaptive risk management Trend Multiplier Enhancement (Both Modes): When strongUpTrend is detected for long positions, the stop loss receives 1.5x breathing room. Strong trends often have deeper retracements before continuing. This is designed to help avoid the strategy being shaken out of active trades by normal market noise. Mode Selection Guidance: - New Users: Start with Fixed Mode for predictable risk levels - Experienced Users: Consider Adaptive Mode for volatility-responsive stops - Volatile Markets: Adaptive Mode may provide better stop placement - Stable Markets: Fixed Mode often sufficient for consistent risk management Early Exit Conditions: Beyond traditional stop losses, QRE implements "smart stops" that trigger before price-based stops: Early Long Exit: (smartScoreLong < 1.0 OR prev5BearCandles) AND realROI < -0.9% 🔄 State Management: The Memory System Complete State Reset Protocol: When a position closes, QRE doesn't just wipe the slate clean – it performs a methodical reset: TP State Cleanup: All Boolean flags: tp1/tp2/tp3HitBefore → FALSE All Reached flags: tp1/tp2/tp3Reached → FALSE All Active flags: tp1/tp2/tp3HoldActive → FALSE Signal Counter Reset: Every one of the 22 signal counters returns to zero. This is designed to avoid signal "ghosting" where old signals influence new trades. Memory Preservation: While operational states reset, certain information is preserved for learning: killReasonLong/Short: Why did this trade end? lastExitWasTP1/TP2/TP3: What was the exit quality? reEntryCount: How many consecutive re-entries have occurred? 🔄 Re-Entry Logic: The Comeback System Re-Entry Conditions Matrix: QRE implements a re-entry system that recognizes not all exits are created equal: TP-Based Re-Entry (Enabled): Criteria: Previous exit was TP1, TP2, or TP3 Cooldown: Minimal or bypassed entirely Logic: Target-based exits indicate potentially viable market conditions EMA-Based Re-Entry (Conditional): Criteria: Previous exit was EMA-based (structural change) Requirements: Must wait for EMA confirmation in new direction Minimum Wait: 5 candles Advanced Re-Entry Features: When adjustReEntryTargets is enabled, the strategy becomes more aggressive with re-entries: Target Adjustment: TP1 multiplied by reEntryTP1Mult (default 2.0) Stop Adjustment: SL multiplied by reEntrySLMult (default 1.5) Logic: If we're confident enough to re-enter, we should be confident enough to hold for bigger moves Performance Tracking: Strategy tracks re-entry win rate, average ROI, and total performance separately from initial entries for optimization analysis. 📊 Exit Reason Analytics: Learning from Every Trade Kill Reason Tracking: Every exit is categorized and stored: "TP3 Exit–Wick Trap": Exit at target level with wick pattern detection "Smart Exit–EMA Down": Structural breakdown exit "Smart Exit–Volatility": Volatility-based protection exit "Exit Post-TP1/TP2/TP3": Standard smart exit progression "Long SL Exit" / "Short SL Exit": Stop loss exits Performance Differentiation: The strategy tracks performance by exit type, allowing for continuous analysis: TP-based exits: Achieved target levels, analyze for pattern improvement EMA-based exits: Mixed results, analyze for pattern improvement SL-based exits: Learning opportunities, adjust entry criteria Volatility exits: Protective measures, monitor performance 🎛️ Trailing Stop Implementation: Conditional Trailing Activation: Activation Criteria: Position profitable beyond trailingStartPct AND (TP hold active OR re-entry trade) Dynamic Trailing Logic: Unlike simple trailing stops, QRE's implementation considers market context: Trending Markets: Wider trail offsets to avoid whipsaws Volatile Markets: Tighter offsets to protect gains Re-Entry Trades: Enhanced trailing to maximize second-chance opportunities Return-to-Entry Protection: When deactivateOnReturn is enabled, the strategy will close positions that return to entry level after being profitable. This is designed to help avoid the frustration of watching profitable trades turn into losers. 🧠 How It All Works Together The beauty of QRE lies not in any single component, but in how everything integrates: The Entry Decision: Multiple pathways are designed to help identify opportunities while maintaining filtering standards. The Progression System: Each TP level unlocks new protection features, like achieving ranks in a video game. The Exit Matrix: Prioritized decision-making aims to reduce analysis paralysis while providing appropriate responses to different market conditions. The Memory System: Learning from each trade while preventing contamination between separate opportunities. The Re-Entry Logic: Re-entry system that balances opportunity with risk management. This creates a trading system where entry conditions filter for quality, progression systems adapt to changing market conditions, exit priorities handle conflicting signals intelligently, memory systems learn from each trade cycle, and re-entry logic maximizes opportunities while managing risk exposure. 📊 ANALYSIS TABLE INTERPRETATION - ⚙️ Enabling Analysis Mode Navigate to strategy settings → "Testing & Analysis" → Enable "Show Analysis Table". The Analysis Table displays different information based on the selected test filter and provides real-time insight into all strategy components, helping users understand current market conditions, position status, and system decision-making processes. 📋 Filter Mode Interpretations "All" Mode (Default View): Composite Section: Buy Score: Aggregated strength from all 22 bullish signals (threshold 5.0+ triggers entry consideration) Sell Score: Aggregated strength from all 22 bearish signals (threshold 5.4+ triggers entry consideration) APEX Filters: ATG Trend: Shows current trend direction analysis Indicates whether momentum filters are aligned for directional bias ReEntry Section: Most Recent Exit: Displays exit type and timeframe since last position closure Status: Shows if ReEntry system is Ready/Waiting/Disabled Count: Current re-entry attempts versus maximum allowed attempts Position Section (When Active): Status: Current position state (LONG/SHORT/FLAT) ROI: Dual calculation showing Custom vs Real ROI percentages Entry Price: Original position entry level Current Price: Live market price for comparison TP Tracking: Progress toward profit targets "Smart" Filter (Critical for Active Positions): Smart Exit Section: Hold Timer: Time elapsed since position opened (bar-based counting) Status: Whether Smart Exit Grid is Enabled/Disabled Score: Current smart score calculation from 22-component matrix Dynamic Threshold: ATR-based minimum score required for holding Final Threshold: Time and ROI-adjusted threshold actually used for decisions Score Check: Pass/Fail based on Score vs Final Threshold comparison Smart Hold: Current hold decision status Final Hold: Final recommendation based on all factors 🎯 Advanced Smart Exit Debugging - ROI & Time-Based Threshold System Understanding the Multi-Layer Threshold System: Layer 1: Dynamic Threshold (ATR-Based) atrRatio = ATR / close dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold (atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard 2.8) // Low volatility: Higher threshold Layer 2: Time Multiplier (ROI & Duration-Based) Winning Positions (ROI ≥ 0%): → timeMultiplier = 1.0 (No time pressure, regardless of hold duration) Losing Positions (ROI < 0%): → holdTimer ≤ 8 bars: timeMultiplier = 1.0 (Early stage, standard requirements) → holdTimer 9-16 bars: timeMultiplier = 1.1 (10% stricter requirements) → holdTimer 17+ bars: timeMultiplier = 1.3 (30% stricter requirements) Layer 3: Final Threshold Calculation finalThreshold = dynamicThreshold × timeMultiplier Examples: - Winning Position: 2.8 × 1.0 = 2.8 (Always standard) - Losing Position (Early): 2.8 × 1.0 = 2.8 (Same as winning initially) - Losing Position (Extended): 2.8 × 1.3 = 3.64 (Much stricter) Real-Time Debugging Display: Smart Exit Section shows: Score: 3.5 → Current smartScoreLong/Short value Dynamic Threshold: 2.8 → Base ATR-calculated threshold Final Threshold: 3.64 (ATR×1.3) → Actual threshold used for decisions Score Check: FAIL (3.5 vs 3.64) → Pass/Fail based on final comparison Final Hold: NO HOLD → Actual system decision Position Status Indicators: Winner + Early: ATR×1.0 (No pressure) Winner + Extended: ATR×1.0 (No pressure - winners can run indefinitely) Loser + Early: ATR×1.0 (Recovery opportunity) Loser + Extended: ATR×1.1 or ATR×1.3 (Increasing pressure to exit) MTF Section: Data Source: Shows whether using MTF Data/EMA Backup/Local EMA Timeframe: Configured watchtower timeframe setting Data Valid: Confirms successful MTF data retrieval status Trend Signal: Higher timeframe directional bias analysis Close Price: MTF price data availability confirmation "Composite" Filter: Composite Section: Buy Score: Real-time weighted scoring from multiple indicators Sell Score: Opposing directional signal strength Threshold: Minimum scores required for signal activation Components: Flash/Blink: Momentum acceleration indicators (F = Flash active, B = Blink active) Individual filter contributions showing which specific signals are firing "ReEntry" Filter: ReEntry System: System: Shows if re-entry feature is Enabled/Disabled Eligibility: Conditions for new entries in each direction Performance: Success metrics of re-entry attempts when enabled 🎯 Key Status Indicators Status Column Symbols: ✓ = Condition met / System active / Signal valid ✗ = Condition not met / System inactive / No signal ⏳ = Cooldown active (waiting period) ✅ = Ready state / Good condition 🔄 = Processing / Transitioning state 🔍 Critical Reading Guidelines For Active Positions - Smart Exit Priority Reading: 1. First Check Position Type: ROI ≥ 0% = Winning Position (Standard requirements) ROI < 0% = Losing Position (Progressive requirements) 2. Check Hold Duration: Early Stage (≤8 bars): Standard multiplier regardless of ROI Extended Stage (9-16 bars): Slight pressure on losing positions Long Stage (17+ bars): Strong pressure on losing positions 3. Score vs Final Threshold Analysis: Score ≥ Final Threshold = HOLD (Continue position) Score < Final Threshold = EXIT (Close position) Watch for timeMultiplier changes as position duration increases 4. Understanding "Why No Hold?" Common scenarios when Score Check shows FAIL: Losing position held too long (timeMultiplier increased to 1.1 or 1.3) Low volatility period (dynamic threshold raised to 2.8) Signal deterioration (smart score dropped below required level) MTF conflict (higher timeframe opposing position direction) For Entry Signal Analysis: Composite Score Reading: Signal strength relative to threshold requirements Component Analysis: Individual filter contributions to overall score EMA Structure: Confirm 3-bar crossover requirement met Cooldown Status: Ensure sufficient time passed since last exit For ReEntry Opportunities (when enabled): System Status: Availability and eligibility for re-engagement Exit Type Analysis: TP-based exits enable immediate re-entry, SL-based exits require cooldown Condition Monitoring: Requirements for potential re-entry signals Debugging Common Issues: Issue: "Score is high but no hold?" → Check Final Threshold vs Score (not Dynamic Threshold) → Losing position may have increased timeMultiplier → Extended hold duration applying pressure Issue: "Why different thresholds for same score?" → Position ROI status affects multiplier → Time elapsed since entry affects multiplier → Market volatility affects base threshold Issue: "MTF conflicts with local signals?" → Higher timeframe trend opposing position → System designed to exit on MTF conflicts → Check MTF Data Valid status ⚡ Performance Optimization Notes For Better Performance: Analysis table updates may impact performance on some devices Use specific filters rather than "All" mode for focused monitoring Consider disabling during live trading for optimal chart performance Enable only when needed for debugging or analysis Strategic Usage: Monitor "Smart" filter when positions are active for exit timing decisions Use "Composite" filter during setup phases for signal strength analysis Reference "ReEntry" filter after position closures for re-engagement opportunities Track Final Threshold changes to understand exit pressure evolution Advanced Debugging Workflow: Position Entry Analysis: Check Composite score vs threshold Verify EMA crossover timing (3 bars prior) Confirm cooldown completion Hold Decision Monitoring: Track Score vs Final Threshold progression Monitor timeMultiplier changes over time Watch for MTF conflicts Exit Timing Analysis: Identify which threshold layer caused exit Track performance by exit type Analyze re-entry eligibility This analysis system provides transparency into strategy decision-making processes, allowing users to understand how signals are generated and positions are managed according to the programmed logic during various market conditions and position states. SIGNAL TYPES AND CHARACTERISTICS 🔥 Core Momentum Signals Flash Signal Calculation: ta.rma(math.abs(close - close ), 5) > ta.sma(math.abs(close - close ), 7) Purpose: Detects sudden price acceleration using smoothed momentum comparison Characteristics: Triggers when recent price movement exceeds historical average movement Usage: Primary momentum confirmation across multiple composite calculations Weight: 1.3 points in composite scoring Blink Signal Calculation: math.abs(ta.change(close, 1)) > ta.sma(math.abs(ta.change(close, 1)), 5) Purpose: Identifies immediate price velocity spikes Characteristics: More sensitive than Flash, captures single-bar momentum bursts Usage: Secondary momentum confirmation, often paired with Flash Weight: 1.3 points in composite scoring ⚡ Advanced Composite Signals Apex Pulse Signal Calculation: apexAngleValue > 30 or apexAngleValue < -30 Purpose: Detects extreme EMA angle momentum Characteristics: Identifies when trend angle exceeds ±30 degrees Usage: Confirms directional momentum strength in trend-following scenarios Pressure Surge Signal Calculation: volSpike_AVP and strongTrendUp_ATG Purpose: Combines volume expansion with trend confirmation Characteristics: Requires both volume spike and strong uptrend simultaneously Usage: bullish signal for trend continuation Shift Wick Signal Calculation: ta.crossunder(ema1, ema2) and isWickTrapDetected and directionFlip Purpose: Detects bearish reversal with wick trap confirmation Characteristics: Combines EMA crossunder with upper wick dominance and directional flip Usage: Reversal signal for trend change identification 🛡️ Trap Exit Protection Signals Bear Trap Exit Calculation: isUpperWickTrap and isBearEngulfNow Conditions: Previous bullish candle with 80%+ upper wick, followed by current bearish engulfing Purpose: Emergency exit signal for long positions Priority: Highest - overrides all other hold conditions Action: Immediate position closure with full state reset Bull Trap Exit Calculation: isLowerWickTrap and isBullEngulfNow Conditions: Previous bearish candle with 80%+ lower wick, followed by current bullish engulfing Purpose: Emergency exit signal for short positions Priority: Highest - overrides all other hold conditions Action: Immediate position closure with full state reset 📊 Technical Analysis Foundation Signals RSI-MFI Hybrid System Base Calculation: (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2 Oversold Threshold: < 35 Overbought Threshold: > 65 Weak Condition: < 35 and declining Strong Condition: > 65 and rising Usage: Momentum confirmation and reversal identification ADX-DMI Trend Classification Strong Up Trend: (adx > 25 and diplus > diminus and (diplus - diminus) > 5) or (ema1 > ema2 and ema2 > ema3 and ta.rising(ema2, 3)) Strong Down Trend: (adx > 20 and diminus > diplus - 5) or (ema1 < ema2 and ta.falling(ema1, 3)) Trend Weakening: adx < adx and adx < adx Usage: Primary trend direction confirmation Bollinger Band Squeeze Detection Calculation: bbWidth < ta.lowest(bbWidth, 20) * 1.2 Purpose: Identifies low volatility periods before breakouts Usage: Entry filter - avoids trades during consolidation 🎨 Visual Signal Indicators Red X Signal Calculation: isBearCandle and ta.crossunder(ema1, ema2) Visual: Red X above price Purpose: Bearish EMA crossunder with confirming candle Composite Weight: +1.0 for short positions, -1.0 for long positions Characteristics: Simple but effective trend change indicator Green Dot Signal Calculation: isBullCandle and ta.crossover(ema1, ema2) Visual: Green dot below price Purpose: Bullish EMA crossover with confirming candle Composite Weight: +1.0 for long positions, -1.0 for short positions Characteristics: Entry confirmation for trend-following strategies Blue Diamond Signal Trigger Conditions: amcBuySignal and score >= 4 Scoring Components: 11 different technical conditions Key Requirements: AMC bullish + momentum rise + EMA expansion + volume confirmation Visual: Blue diamond below price Purpose: Bullish reversal or continuation signal Characteristics: Multi-factor confirmation requiring 4+ technical alignments Red Diamond Signal Trigger Conditions: amcSellSignal and score >= 5 Scoring Components: 11 different technical conditions (stricter than Blue Diamond) Key Requirements: AMC bearish + momentum crash + EMA compression + volume decline Visual: Red diamond above price Purpose: Potential bearish reversal or continuation signal Characteristics: Requires higher threshold (5 vs 4) for more selective triggering 🔵 Specialized Detection Signals Blue Dot Signal Calculation: volumePulse and isCandleStrong and volIsHigh Requirements: Volume > 2.0x MA, strong candle body > 35% of range, volume MA > 55 Purpose: Volume-confirmed momentum signal Visual: Blue dot above price Characteristics: Volume-centric signal for high-liquidity environments Orange X Signal Calculation: Complex multi-factor oversold reversal detection Requirements: AMC oversold + wick trap + flash/blink + RSI-MFI oversold + bullish flip Purpose: Oversold bounce signal with multiple confirmations Visual: Orange X below price Characteristics: Reversal signal requiring 5+ simultaneous conditions VSS (Velocity Signal System) Components: Volume spike + EMA angle + trend direction Buy Signal: vssTrigger and vssTrendDir == 1 Sell Signal: vssTrigger and vssTrendDir == -1 Visual: Green/Red triangles Purpose: Velocity-based momentum detection Characteristics: Fast-response signal for momentum trading ⭐ Elite Composite Signals Star Uprising Signal Base Requirements: entryCompositeBuySignal and echoBodyLong and strongUpTrend and isAMCUp Additional Confirmations: RSI hybrid strong + not high risk Special Conditions: At bottom zone OR RSI bottom bounce OR strong volume bounce Visual: Star symbol below price Purpose: Bullish reversal signal from oversold conditions Characteristics: Most selective bullish signal requiring multiple confirmations Ultra Short Signal Scoring System: 7-component scoring requiring 4+ points Key Components: EMA trap + volume decline + RSI weakness + composite confirmation Additional Requirements: Falling EMA structure + volume spike + flash confirmation Visual: Explosion emoji above price Purpose: Aggressive short entry for trend reversal or continuation Characteristics: Complex multi-layered signal for experienced short selling 🎯 Composite Signal Architecture Enhanced Composite Scoring Long Composite: 15+ weighted components including structure, momentum, flash/blink, volume, price action, reversal triggers, trend alignment Short Composite: Mirror structure with bearish bias Threshold: 5.0 points required for signal activation Conflict Resolution: If both long and short signals trigger simultaneously, both are disabled Final Validation: Requires EMA momentum confirmation (ta.rising(emaFast_ATG, 2) for longs, ta.falling(emaFast_ATG, 2) for shorts) Risk Assessment Integration High Risk Long: RSI > 70 OR close > upper Bollinger Band 80% High Risk Short: RSI < 30 OR close < lower Bollinger Band 80% Zone Analysis: Top zone (95% of 50-bar high) vs Bottom zone (105% of 50-bar low) Risk Penalty: High risk conditions subtract 1.5 points from composite scores This signal architecture creates a multi-layered detection system where simple momentum signals provide foundation, technical analysis adds structure, visual indicators offer clarity, specialized detectors capture different market conditions, and composite signals identify potential opportunities while integrated risk assessment is designed to filter risky entries. VISUAL FEATURES SHOWCASE Ichimoku Cloud Visualization Dynamic Color Intensity: Cloud transparency adapts to momentum strength - darker colors indicate stronger directional moves, while lighter transparency shows weakening momentum phases. Gradient Color Mapping: Bullish momentum renders blue-purple spectrum with increasing opacity, while bearish momentum displays corresponding color gradients with intensity-based transparency. Real-time Momentum Feedback: Color saturation provides immediate visual feedback on market structure strength, allowing traders to assess levels at a glance without additional indicators. EMA Ribbon Bands The 8-level exponential moving average system creates a comprehensive trend structure map with gradient color coding. Signal Type Visualization STRATEGY PROPERTIES & BACKTESTING DISCLOSURE 📊 Default Strategy Configuration: ✅ Initial Capital: 100,000 USD (realistic for average traders) ✅ Commission: 0.075% per trade (realistic exchange fees) ✅ Slippage: 3 ticks (market impact consideration) ✅ Position Size: 5% equity per trade (sustainable risk level) ✅ Pyramiding: Disabled (single position management) ✅ Sample Size: 185 trades over 12-month backtesting period ✅ Risk Management: Adaptive stop loss with maximum 1% risk per trade COMPREHENSIVE BACKTESTING RESULTS Testing Period & Market Conditions: Backtesting Period: June 25, 2024 - June 25, 2025 (12 months) Timeframe: 15-minute charts (MTF system active) Market: BTCUSDT (Bitcoin/Tether) Market Conditions: Full market cycle including volatility periods Deep Backtesting: Enabled for maximum accuracy 📈 Performance Summary: Total Return: +2.19% (+2,193.59 USDT) Total Trades Executed: 185 trades Win Rate: 34.05% (63 winning trades out of 185) Profit Factor: 1.295 (gross profit ÷ gross loss) Maximum Drawdown: 0.65% (653.17 USDT) Risk-Adjusted Returns: Consistent with conservative risk management approach 📊 Detailed Trade Analysis: Position Distribution: Long Positions: 109 trades (58.9%) | Win Rate: 36.70% Short Positions: 76 trades (41.1%) | Win Rate: 30.26% Average Trade Duration: Optimized for 15-minute timeframe efficiency Profitability Metrics: Average Profit per Trade: 11.74 USDT (0.23%) Average Winning Trade: 151.17 USDT (3.00%) Average Losing Trade: 60.27 USDT (1.20%) Win/Loss Ratio: 2.508 (winners are 2.5x larger than losses) Largest Single Win: 436.02 USDT (8.69%) Largest Single Loss: 107.41 USDT (controlled risk management) 💰 Financial Performance Breakdown: Gross Profit: 9,523.93 USDT (9.52% of capital) Gross Loss: 7,352.48 USDT (7.35% of capital) Net Profit After Costs: 2,171.44 USDT (2.17%) Commission Costs: 1,402.47 USDT (realistic trading expenses) Maximum Equity Run-up: 2,431.66 USDT (2.38%) ⚖️ Risk Management Validation: Maximum Drawdown: 0.65% showing controlled risk management Drawdown Recovery: Consistent equity curve progression Risk per Trade: Successfully maintained below 1.5% per position Position Sizing: 5% equity allocation proved sustainable throughout testing period 📋 Strategy Performance Characteristics: ✅ Strengths Demonstrated: Controlled Risk: Maximum drawdown well below industry standards (< 1%) Positive Expectancy: Win/loss ratio of 2.5+ creates profitable edge Consistent Performance: Steady equity curve without extreme volatility Realistic Costs: Includes actual commission and slippage impacts Sample Size: 185 trades during testing period ⚠️ Performance Considerations: Win Rate: 34% win rate requires discipline to follow system signals Market Dependency: Performance may vary significantly in different market conditions Timeframe Sensitivity: Optimized for 15-minute charts; other timeframes may show different results Slippage Impact: Real trading conditions may affect actual performance 📊 Benchmark Comparison: Strategy Return: +2.19% over 12 months Buy & Hold Bitcoin: +71.12% over same period Strategy Advantage: Significantly lower drawdown and volatility Risk-Adjusted Performance: Different risk profile compared to holding cryptocurrency 🎯 Real-World Application Insights: Expected Trading Frequency: Average: 15.4 trades per month (185 trades ÷ 12 months) Weekly Frequency: Approximately 3-4 trades per week Active Management: Requires regular monitoring during market hours Capital Requirements: Minimum Used in Testing: $10,000 for sustainable position sizing Tested Range: $50,000-$100,000 for comfortable risk management Commission Impact: 0.075% per trade totaled 1.4% of capital over 12 months ⚠️ IMPORTANT BACKTESTING DISCLAIMERS: 📈 Performance Reality: Past performance does not guarantee future results. Backtesting results represent hypothetical performance and may not reflect actual trading outcomes due to market changes, execution differences, and emotional factors. 🔄 Market Condition Dependency: This strategy's performance during the tested period may not be representative of performance in different market conditions, volatility regimes, or trending vs. sideways markets. 💸 Cost Considerations: Actual trading costs may vary based on broker selection, market conditions, and trade size. Commission rates and slippage assumptions may differ from real-world execution. 🎯 Realistic Expectations: The 34% win rate requires psychological discipline to continue following signals during losing streaks. Risk management and position sizing are critical for replicating these results. ⚡ Technology Dependencies: Strategy performance assumes reliable internet connection, platform stability, and timely signal execution. Technical failures may impact actual results. CONFIGURATION OPTIMIZATION 5-Minute Timeframe Optimization (Advanced Users Only) ⚠️ Important Warning: 5-minute timeframes operate without MTF confirmation, resulting in reduced signal quality and higher false signal rates. Example 5-Minute Parameters: Composite Thresholds: Long 6.5, Short 7.0 (vs 15M default 5.0/5.4) Signal Lookback Bars: 12 (vs 15M default 8) Volume Multiplier: 2.2 (vs 15M default 1.8) MTF Timeframe: Disabled (automatic below 30M) Risk Management Adjustments: Position Size: Reduce to 3% (vs 5% default) TP1: 0.8%, TP2: 1.2%, TP3: 2.0% (tighter targets) SL: 0.8% (tighter stop loss) Cooldown Minutes: 8 (vs 5 default) Usage Notes for 5-Minute Trading: - Wait for higher composite scores before entry - Require stronger volume confirmation - Monitor EMA structure more closely 15-Minute Scalping Setup: TP1: 1.0%, TP2: 1.5%, TP3: 2.5% Composite Threshold: 5.0 (higher filtering) TP ATR Multiplier: 7.0 SL ATR Multiplier: 2.5 Volume Multiplier: 1.8 (requires stronger confirmation) Hold Time: 2 bars minimum 3-Hour Swing Setup: TP1: 2.0%, TP2: 4.0%, TP3: 8.0% Composite Threshold: 4.5 (more signals) TP ATR Multiplier: 8.0 SL ATR Multiplier: 3.2 Volume Multiplier: 1.2 Hold Time: 6 bars minimum Market-Specific Adjustments High Volatility Periods: Increase ATR multipliers (TP: 2.0x, SL: 1.2x) Raise composite thresholds (+0.5 points) Reduce position size Enable cooldown periods Low Volatility Periods: Decrease ATR multipliers (TP: 1.2x, SL: 0.8x) Lower composite thresholds (-0.3 points) Standard position sizing Disable extended cooldowns News Events: Temporarily disable strategy 30 minutes before major releases Increase volume requirements (2.0x multiplier) Reduce position sizes by 50% Monitor for unusual price action RISK MANAGEMENT Dual ROI System: Adaptive vs Fixed Mode Adaptive RR Mode: Uses ATR (Average True Range) for automatic adjustment TP1: 1.0x ATR from entry price TP2: 1.5x ATR from entry price TP3: 2.0x ATR from entry price Stop Loss: 1.0x ATR from entry price Automatically adjusts to market volatility Fixed Percentage Mode: Uses predetermined percentage levels TP1: 1.0% (default) TP2: 1.5% (default) TP3: 2.5% (default) Stop Loss: 0.9% total (0.6% risk tolerance + 0.3% slippage buffer)(default) Consistent levels regardless of volatility Mode Selection: Enable "Use Adaptive RR" for ATR-based targets, disable for fixed percentages. Adaptive mode works better in varying volatility conditions, while fixed mode provides predictable risk/reward ratios. Stop Loss Management In Adaptive SL Mode: Automatically scales with market volatility Tight stops during low volatility (smaller ATR) Wider stops during high volatility (larger ATR) Include 0.3% slippage buffer in both modes In Fixed Mode: Consistent percentage-based stops 2% for crypto, 1.5% for forex, 1% for stocks Manual adjustment needed for different market conditions Trailing Stop System Configuration: Enable Trailing: Activates dynamic stop loss adjustment Start Trailing %: Profit level to begin trailing (default 1.0%) Trailing Offset %: Distance from current price (default 0.5%) Close if Return to Entry: Optional immediate exit if price returns to entry level Operation: Once position reaches trailing start level, stop loss automatically adjusts upward (longs) or downward (shorts) maintaining the offset distance from favorable price movement. Timeframe-Specific Risk Considerations 15-Minute and Above (Tested): ✅ Full MTF system active ✅ Standard risk parameters apply ✅ Backtested performance metrics valid ✅ Standard position sizing (5%) 5-Minute Timeframes (Advanced Only): ⚠️ MTF system inactive - local signals only ⚠️ Higher false signal rate expected ⚠️ Reduced position sizing preferred (3%) ⚠️ Tighter stop losses required (0.8% vs 1.2%) ⚠️ Requires parameter optimization ⚠️ Monitor performance closely 1-Minute Timeframes (Limited Testing): ❌ Excessive noise levels ❌ Strategy not optimized for this frequency Risk Management Practices Allocate no more than 5% of your total investment portfolio to high-risk trading Never trade with funds you cannot afford to lose Thoroughly backtest and validate the strategy with small amounts before full implementation Always maintain proper risk management and stop-loss settings IMPORTANT DISCLAIMERS Performance Disclaimer Past performance does not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice. Market Risk Cryptocurrency and forex markets are highly volatile. Prices can move rapidly against positions, resulting in significant losses. Users should never risk more than they can afford to lose. Strategy Limitations This strategy relies on technical analysis and may not perform well during fundamental market shifts, news events, or unprecedented market conditions. No trading strategy can guarantee 100% success or eliminate the risk of loss. Legal Compliance You are responsible for compliance with all applicable regulations and laws in your jurisdiction. Consult with licensed financial professionals when necessary. User Responsibility Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
Стратегия Pine Script®
от ApexLegion
2
RC - Crypto Scalper v3Cryptocurrency scalping strategy for perpetual futures with risk management and automation capabilities. ## Strategy Overview This strategy identifies high-probability scalping opportunities in cryptocurrency perpetual futures markets using adaptive position sizing, dynamic stop losses, and intelligent exit management to maintain consistent risk-adjusted returns across varying market conditions. ## Technical Foundation The strategy employs exponential moving averages for trend detection, Bollinger Bands for volatility measurement and mean reversion signals, RSI for momentum confirmation and overbought/oversold conditions, ATR for dynamic volatility-based stop placement, and VWAP for institutional price level identification. These technical indicators are combined with volume analysis and optional multi-timeframe confirmation to filter low-probability setups. ## Entry Methodology The strategy identifies trading opportunities using three complementary approaches that can be enabled individually or in combination: Momentum-Based Entries: Detects directional price movements aligned with short-term and intermediate-term trend indicators, with momentum oscillator confirmation to avoid entries at exhaustion points. Volume analysis provides additional confirmation of institutional participation. Mean Reversion Entries: Identifies price extremes using statistical volatility bands combined with momentum divergence, targeting high-probability reversal zones in ranging market conditions. Entries require initial price structure confirmation to reduce false signals. Institutional Flow Entries: Monitors volume-weighted price levels to identify areas where institutional orders are likely concentrated, entering on confirmed breaks of these key levels with supporting directional bias from trend indicators. Each methodology uses distinct combinations of the technical indicators mentioned above, with specific parameter relationships and confirmation requirements that can be customized based on trader preference and market conditions. ## Exit Framework Adaptive Stop Loss: Uses ATR-based stops (default 0.7x multiplier on 14-period ATR) that automatically adjust to current market volatility. Stop distance expands during volatile periods to avoid premature stops while tightening during consolidation to protect capital. Alternative percentage-based stops available for traders preferring fixed-distance risk management. Trailing Profit System: Employs a dual-target exit approach combining fixed limit orders with dynamic trailing stops. The system activates trailing stops when positions reach profitable thresholds, allowing winning trades to capture extended moves while protecting accumulated gains. The high fixed limit (6R default) serves as a ceiling for exceptional moves while the trailing mechanism handles the majority of exits at optimal profit levels. Time-Based Management: Implements maximum holding period constraints (50 bars default) to prevent capital from being trapped in directionless price action. This ensures consistent capital turnover and prevents the strategy from holding through extended consolidation periods. Breakeven Protection: Automatically adjusts stop loss to entry price plus commission costs once trades reach predefined profit thresholds (0.7R default), eliminating downside risk on positions that have demonstrated directional follow-through. ## Risk Management Position Sizing: Dynamic position sizing based on account equity percentage risk model (2% default). Calculates optimal position size based on entry price, stop distance, and account risk tolerance. Includes maximum position exposure caps and minimum position size thresholds to ensure practical trade execution. Daily Loss Limits: Automatic trading suspension when intraday losses exceed configured threshold (5% of equity default). Prevents catastrophic drawdown days and removes emotional decision-making during adverse market conditions. Resets automatically at the start of each new trading day. Leverage Controls: Comprehensive leverage monitoring with built-in liquidation protection for margined positions. Strategy calculates liquidation prices based on leverage settings and automatically closes positions approaching critical margin levels, preventing forced liquidations. Exposure Management: Multiple layers of position size controls including maximum position value as percentage of equity (50% default), leverage-adjusted margin requirements, and minimum capital availability thresholds before opening new positions. ## Market Filters Session-Based Filtering: Configurable trading windows for Asian (00:00-08:00 UTC), London (08:00-16:00 UTC), and New York (13:00-21:00 UTC) sessions. Allows traders to focus on specific market hours or avoid illiquid periods based on their asset and trading style. Volatility Requirements: Minimum and maximum ATR percentage thresholds ensure strategy only operates within optimal volatility ranges. Prevents trading during both insufficient movement periods and extreme volatility events where execution quality deteriorates. Trend Alignment: Optional higher timeframe trend filter ensures directional bias aligns with broader market structure, reducing counter-trend entries during strong directional moves. Volume Confirmation: Configurable volume requirements for entry validation, ensuring sufficient market participation and reducing false signals during low-liquidity periods. ## Automation Support Built-in webhook integration generates JSON payloads compatible with popular broker automation platforms. Alert system provides comprehensive notifications for all entry signals, exit executions, risk limit breaches, and daily trading status updates. Supports both automated and manual execution workflows. ## Settings Explanation Initial Capital: $5,000 Selected as realistic starting point for retail traders entering crypto futures markets. Strategy scales proportionally - larger accounts show similar percentage returns with proportionally larger absolute gains and position sizes. Risk Per Trade: 2% Conservative default providing significant drawdown tolerance. With 51% historical win rate and positive expectancy, risking 2% per trade allows for extended losing streaks without account impairment. Adjustable from 0.5% (very conservative) to 5% (aggressive, experienced traders only). Leverage: 10x Standard cross-margin leverage for cryptocurrency perpetual futures. Combined with 2% risk setting and maximum 50% equity position size caps, actual exposure remains controlled despite leverage. Built-in liquidation protection provides additional safety layer. Commission: 0.055% Modeled on major exchange maker fee structures (Bybit, Binance Futures). **Slippage: 50 ticks** Ultra-conservative slippage assumption representing extreme worst-case execution scenarios. ETH perpetual tick size is $0.01, therefore 50 ticks equals $0.50 per side or $1.00 round trip slippage per trade. Real-world slippage on 30-minute timeframe typically ranges from 2-5 ticks ($0.02-0.05 round trip) under normal conditions, with 10-20 ticks during highly volatile periods. The 50-tick setting assumes every single trade executes during extreme market stress conditions. This ultra-conservative modeling approach means real-world trading performance under typical market conditions may exceed backtest results, as the strategy has been tested under punishing execution cost assumptions that represent worst-case scenarios rather than expected outcomes. Stop Loss: ATR-based (0.7x multiplier) Volatility-adaptive stops optimized for 30-minute cryptocurrency perpetuals. The 0.7x multiplier balances protection against premature stops due to normal market noise. Lower multipliers (0.5-0.6x) suitable for lower timeframes, higher multipliers (0.8-1.2x) for higher timeframes. Take Profit: 6R (Risk:Reward) High target designed to work in conjunction with trailing stop system rather than as primary exit mechanism. Historical analysis shows most profitable trades exit via trailing stops at lower multiples, with the 6R limit capturing occasional extended moves. This configuration allows the trailing stop system to operate optimally while providing upside capture on exceptional price runs. Trailing Stop: Activates at 1R | Offset 0.5R Trailing mechanism engages when position reaches 1:1 risk-reward, then maintains 0.5R distance from peak favourable price. This configuration allows profitable trades room to develop while protecting accumulated gains from reversals. Maximum Holding Period: 50 bars Automatic exit trigger after 50 bars (25 hours on 30-minute timeframe) prevents capital commitment to non-trending price action. Adjustable based on timeframe and trading style preferences. ## Backtest Performance Test Period: November 2023 - November 2025 (2 years) Asset: ETH/USDT Perpetual Futures Timeframe: 30 minutes Initial Capital: $5,000 Performance Metrics: - Final Equity: $25,353.99 - Net Profit: $20,353.99 - Total Return: 407.08% - Annualized Return: ~204% - Total Trades: 2,549 - Winning Trades: 1,308 (51.28%) - Losing Trades: 1,241 (48.72%) - Profit Factor: 1.215 - Sharpe Ratio: 0.813 - Sortino Ratio: 6.428 - Maximum Drawdown: 11.53% - Average Drawdown: <2% Trade Statistics: - Average Win: 1.15% per trade - Average Loss: -0.98% per trade - Win/Loss Ratio: 1.17:1 - Largest Win: 7.14% - Largest Loss: -2.31% - Average Trade Duration: ~8 hours - Trades Per Month: ~106 Cost Analysis: - Total Commission Paid: $21,277.06 - Commission as % of Gross Profit: 18.5% - Modeled Slippage Impact: $2,549.00 (50 ticks per trade) - Total Trading Costs: $23,826.06 - Net Profit After All Costs: $20,353.99 Risk-Adjusted Performance: - Return/Max DD Ratio: 35.3 - Profit Per Trade: $7.98 average - Risk of Ruin: <0.001% (with 2% risk, 51% win rate, 1.17 R:R) ## Bear Market Validation To validate robustness across different market conditions, the strategy was additionally tested during the 2022 cryptocurrency bear market: Test Period: May 2022 - November 2022 (7 months) Market Conditions: ETH declined 57% (from ~$2,900 to ~$1,200) Bear Market Results: - Net Profit: $4,959.69 - Return: 99.19% - Total Trades: 845 - Win Rate: 51.72% - Maximum Drawdown: 18.54% - Profit Factor: 1.235 - Outperformance vs Buy & Hold: +156.3% The strategy demonstrated profitable performance during severe market decline, with short positions showing particular strength (54.1% win rate on shorts vs 49.4% on longs). This validates that the edge is not dependent on bullish market conditions and the multiple entry methodologies adapt naturally to different market environments. ## Recommended Usage Optimal Timeframes: - Primary: 30-minute (tested and optimized) - Alternative: 1-hour (more selective, fewer trades) - Not recommended: <15-minute (execution quality deteriorates) Suitable Assets: High-liquidity cryptocurrency perpetual futures recommended: - BTC/USDT (>$2B daily volume) - ETH/USDT (>$1B daily volume) - SOL/USDT, AVAX/USDT (>$100M daily volume) - Avoid low-liquidity pairs (<$50M daily volume) Risk Configuration: - Conservative: 1-1.5% per trade - Moderate: 2-3% per trade (default: 2%) - Aggressive: 3-5% per trade (requires discipline) ## Important Considerations Backtesting vs Live Trading: Always paper trade first. Real-world results vary based on execution quality, broker-specific factors, network latency, and individual trade management decisions. Backtest performance represents historical simulation with ultra-conservative cost assumptions, not guaranteed future results. Market Conditions: Strategy designed for liquid, actively-traded markets. Performance characteristics: - Strong trends: Optimal (trailing stops capture extended moves) - Ranging markets: Moderate (mean reversion component provides edge) - Low volatility: Reduced (ATR filter prevents most entries) - Extreme volatility: Protected (maximum volatility filter prevents entries) Cost Impact: Commission represents approximately 18.5% of gross profit in backtests. The 50-tick slippage assumption is deliberately punitive - typical execution will likely be 5-10x better (2-10 ticks actual vs 50 ticks modeled), meaning real-world net results may significantly exceed backtest performance under normal market conditions. Execution Quality: 30-minute timeframe provides sufficient time for order placement and management. Automated execution recommended for consistency. Manual execution requires discipline to follow signals without hesitation or second-guessing. Starting Procedures: 1. Run backtest on your specific asset and timeframe 2. Paper trade for minimum 50 trades or 2 weeks 3. Start with minimum position sizes (0.5-1% risk) 4. Gradually scale to target risk levels as confidence builds 5. Monitor actual execution costs vs backtest assumptions ## Strategy Limitations - Requires liquid markets; performance degrades significantly on low-volume pairs - No built-in news event calendar; traders should manually avoid scheduled high-impact events - Weekend/holiday trading may experience wider spreads and different price behaviour - Does not model spread costs (assumes mid-price fills); add 1-2 ticks additional cost for market orders - Performance during market structure changes (regime shifts) may differ from backtest period - Requires consistent monitoring during active trading hours for optimal automated execution - Slippage assumptions are deliberately extreme; actual slippage will typically be much lower ## Risk Disclosure Cryptocurrency trading involves substantial risk of loss. Leverage amplifies both gains and losses. This strategy will experience losing streaks and drawdowns. The 11.53% maximum historical drawdown in bull market testing and 18.54% in bear market testing do not represent ceilings - larger drawdowns are possible and should be expected in live trading. Past performance does not guarantee future results. Market conditions evolve, and historical edge may diminish or disappear. No strategy works in all market conditions. The strategy has been tested with extremely conservative slippage assumptions (50 ticks per trade) that significantly exceed typical execution costs; this provides a safety margin but does not eliminate risk. Capital at Risk: Only trade with capital you can afford to lose completely. The strategy's positive historical performance across both bull and bear markets does not eliminate the possibility of significant losses or account impairment. Not Financial Advice: This strategy is an educational tool, not investment advice. Users are solely responsible for their trading decisions, risk management, and outcomes. The developer assumes no liability for trading losses. Leverage Warning: Trading with leverage can result in losses exceeding initial investment. Ensure you understand leverage mechanics and liquidation risks before using leveraged products. ## Technical Requirements - TradingView Premium subscription (for strategy testing and alerts) - Understanding of risk management principles - Familiarity with perpetual futures mechanics - Broker account supporting crypto perpetuals (if trading live) - For automation: Webhook-compatible execution platform ## Version History v3.0 - November 2025 (Initial Release) - Multi-methodology entry system (Momentum, Mean Reversion, VWAP) - Comprehensive risk management framework - Adaptive exit system with trailing stops - Session and volatility filtering - Webhook automation support - Validated across bull market (2024-25) and bear market (2022) periods - Tested with ultra-conservative 50-tick slippage assumptions Disclaimer: This strategy is provided "as-is" for educational purposes. Past performance does not indicate future results. All backtests conducted with 50-tick slippage (ultra-conservative assumptions). Actual trading costs typically significantly lower. Trade responsibly and at your own risk.
Стратегия Pine Script®
от RealisticCrypto1
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy? The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach. It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation. Ideal for swing traders seeking to ride strong trends while managing risk. ---- How does the strategy work? The strategy follows a systematic process to capture high-momentum breakouts: Pre-Breakout Criteria: Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles). Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation. Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend. Price Break: Enters when price clears the consolidation high with conviction. Risk Management: Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside. Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run. Trailing Stop (Unique Edge): Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms. Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns. ---- What markets or timeframes is this suited for? This is a long-only strategy designed for trending markets, and it performs best in: Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures). Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends. Key Advantage: The TradingView script allows instant backtesting with adjustable parameters You can: - Test historical performance across multiple markets to identify which assets align best with the strategy. - Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile. Build a diversified portfolio by filtering for markets that show consistent profitability in backtests. For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently. ---- What indicators or tools does the strategy use? The strategy combines customizable technical tools with strict anti-lookahead safeguards: Core Indicators: Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets. Breakout Parameters: Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern. Entry Models: Flexible entry logics (Breakouts and fractals) Anti-Lookahead Design: All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal. ---- How do I manage risk with this strategy? The strategy prioritizes customizable risk controls to align with your trading style and account size: User-Defined Risk Inputs: Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade. Flexibility: Choose between fixed risk or equity-based scaling. The script adjusts position sizing dynamically based on your selection. Pyramiding Feature: Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact. Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk. Risk-Free Trade Mechanic: Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk. The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable. Impact on Net Profit & Drawdown: Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach. Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity. Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly. ---- How does the strategy identify market structure for its trailing stoploss? The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed. ---- What are the underlying calculations? The underlying calculations involve: Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it. Break of Structure (BOS): Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend. Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend. Structural Liquidity and Invalidation: Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS. Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend. This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages. By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool. ---- What entry criteria are used in this script? The script uses two entry models for trading decisions: BreakOut and Fractal. Underlying Calculations: Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade. Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern. ---- What type of stop-loss identification method are used in this strategy? This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss. Underlying Calculations: Initial Stop-loss: ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction. Calculation: - First, the True Range (TR) is calculated for each period, which is the greatest of: - Current Period High - Current Period Low - Absolute Value of Current Period High - Previous Period Close - Absolute Value of Current Period Low - Previous Period Close - The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility. Swing Low Based: For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss. Trailing Stop-Loss: The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves: Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement. Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses. By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably. Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels. Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns. ---- What type of break-even method is used in this strategy? What are the underlying calculations? Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio. Calculation: Break-even level = Entry Price + (Initial Risk * RR Ratio) ---- What tables are available in this script? - Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more. Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart. Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability. Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit. MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position. Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses. Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit. Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control. BE Trades: Number of break-even trades, excluding commission/slippage. Losing Trades: The total number of losing trades generated by the strategy. Winning Trades: The total number of winning trades generated by the strategy. Total Trades: Total number of taken traders visible your charts. Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign. - Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year. - Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations. - UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S. User-input styles and customizations: Please note that all background colors in the style are disabled by default to enhance visualization. How to Use This Strategy to Create a Profitable Edge and Systems? Choose Your Strategy mode: - Decide whether you are creating an investing strategy or a trading strategy. Select a Market: - Choose a one-sided market such as stocks, indices, or cryptocurrencies. Historical Data: - Ensure the historical data covers at least 10 years of price action for robust backtesting. Timeframe Selection: - Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits. Set Commission and Slippage: - Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications. Parameter Optimization: - Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester. Trade Count: - Ensure the number of trades is 200 or more; the higher, the better for statistical significance. Positive Average Trade: - Make sure the average trade is above zero. (An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.) Performance Metrics: - Look for a high profit factor, and net profit with minimum drawdown. - Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance. Refinement and Optimization: - Try out different markets and timeframes. - Continue working on refining your edge using the available filters and components to further optimize your strategy. What Makes This Strategy Unique? This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical: 1. Adapts to Any Market Rhythm Works on daily, weekly, or intraday charts without code changes. Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts). 2. Smarter Stop-Loss System No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages. Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets. 3. Safe Profit-Boosting Pyramiding Adds new positions only after prior trades are risk-free (stops moved above breakeven). Scales up using locked-in profits, not new capital, to grow gains safely. 4. Built-In Momentum Check Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum. Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited. - By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Стратегия Pine Script®
от Fractalyst
3
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE) Pure Signal Evolution Through Genetic Algorithms Where Darwin Meets Technical Analysis 🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control . What This Indicator Does: Generates Long/Short entry signals with probability scores (35-88% range) Evolves a population of up to 12 competing strategies using genetic algorithms Validates strategies through walk-forward optimization (train/test cycles) Visualizes signal quality through premium gradient clouds and confidence halos Displays comprehensive metrics via enhanced dashboard Provides alerts for entries and exits Works on any timeframe, any instrument, any broker What This Indicator Does NOT Do: Execute trades automatically Manage positions or calculate position sizes Place orders on your behalf Make trading decisions for you This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade. 🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS What Makes This Different - The Evolutionary Foundation Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles: Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency) Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals. 🧪 THE DNA: WHAT EVOLVES Every strategy carries a 10-gene chromosome controlling how it interprets market data: Signal Sensitivity Genes Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals. Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups. Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters. Probability Adjustment Genes Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic. Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets. Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important. Risk Management Genes ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR. Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room. Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds. Adaptation Gene Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes. The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe. 📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence: Layer 1 - Market Entropy (Information Theory) Measures whether price movements exhibit directional order or random walk characteristics: The Math: Shannon Entropy = -Σ(p × log(p)) Market Order = 1 - (Entropy / 0.693) What It Means: High entropy = choppy, random market → low confidence signals Low entropy = directional market → high confidence signals Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars) Signal Output: -1.0 to +1.0 (bearish order to bullish order) Layer 2 - Momentum Synthesis Combines three momentum indicators into single composite score: Components: RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50 Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1 MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives. Signal Output: -1.0 to +1.0 (strong bearish to strong bullish) Layer 3 - Structure Analysis Evaluates price position within swing range (default: 50-bar lookback): Position Classification: Bottom 20% of range = Support Zone → bullish bounce potential Top 20% of range = Resistance Zone → bearish rejection potential Middle 60% = Neutral Zone → breakout/breakdown monitoring Signal Logic: At support + bullish candle = +0.7 (strong buy setup) At resistance + bearish candle = -0.7 (strong sell setup) Breaking above range highs = +0.5 (breakout confirmation) Breaking below range lows = -0.5 (breakdown confirmation) Consolidation within range = ±0.3 (weak directional bias) Signal Output: -1.0 to +1.0 (bearish structure to bullish structure) Confluence Voting System Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal: Examples: Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes) Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote) All three bullish → Signal generated with +5% probability bonus This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy. 📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED Base Probability: Raw_Prob = 50% + (Average_Signal_Strength × 25%) Then AGE applies strategic adjustments: Trend Alignment: Signal with trend: +4% Signal against strong trend: -8% Weak/no trend: no adjustment Regime Adaptation: Trending market (efficiency >50%, moderate vol): +3% Volatile market (vol ratio >1.5x): -5% Choppy market (low efficiency): -2% Volume Confirmation: Volume > 70% of 20-bar SMA: no change Volume below threshold: -3% Volatility State (DVS Ratio): High vol (>1.8x baseline): -4% (reduce confidence in chaos) Low vol (<0.7x baseline): -2% (markets can whipsaw in compression) Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging) Confluence Bonus: All 3 indicators agree: +5% 2 of 3 agree: +2% Strategy Gene Adjustment: Probability Boost gene: -10% to +10% Regime Adaptation gene: scales regime adjustments by 0-100% Final Probability: Clamped between 35% (minimum) and 88% (maximum) Why These Ranges? Below 35% = too uncertain, better not to signal Above 88% = unrealistic, creates overconfidence Sweet spot: 65-80% for quality entries 🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE Each active strategy maintains a virtual trading account that executes in parallel with real-time data: Shadow Trading Mechanics Entry Logic: Calculate signal direction, probability, and confluence using strategy's unique DNA Check if signal meets quality gate: Probability ≥ configured minimum threshold (default: 65%) Confluence ≥ configured minimum (default: 2 of 3) Direction is not zero (must be long or short, not neutral) Verify signal persistence: Base requirement: 2 bars (configurable 1-5) Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1 Apply additional filters: Trend strength must exceed strategy's requirement gene Regime filter: if volatile market detected, probability must be 72%+ to override Volume confirmation required (volume > 70% of average) If all conditions met for required persistence bars, enter shadow position at current close price Position Management: Entry Price: Recorded at close of entry bar Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio Position: +1 (long) or -1 (short), only one at a time per strategy Exit Logic: Check if price hit stop (on low) or target (on high) on current bar Record trade outcome in R-multiples (profit/loss normalized by ATR) Update performance metrics: Total trades counter incremented Wins counter (if profit > 0) Cumulative P&L updated Peak equity tracked (for drawdown calculation) Maximum drawdown from peak recorded Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed Reset signal age counter to zero Walk-Forward Tracking: During position lifecycle, trades are categorized: Training Phase (first 250 bars): Trade counted toward training metrics Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample) Live Phase (after WFO period): Trade counted toward overall metrics Why Shadow Portfolios? No lookahead bias (uses only data available at the bar) Realistic execution simulation (entry on close, stop/target checks on high/low) Independent performance tracking for true fitness comparison Allows safe experimentation without risking capital Each strategy learns from its own experience 🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system: Core Metrics (Minimum 3 trades required) Win Rate (30% of fitness): WinRate = Wins / TotalTrades Normalized directly (0.0-1.0 scale) Total P&L (30% of fitness): Normalized_PnL = (PnL + 300) / 600 Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale. Expectancy (25% of fitness): Expectancy = Total_PnL / Total_Trades Normalized_Expectancy = (Expectancy + 30) / 60 Clamped 0.0-1.0. Rewards consistency of profit per trade. Drawdown Control (15% of fitness): Normalized_DD = 1 - (Max_Drawdown / 15) Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak. Sample Size Adjustment Quality Factor: <50 trades: 1.0 (full weight, small sample) 50-100 trades: 0.95 (slight penalty for medium sample) 100 trades: 0.85 (larger penalty for large sample) Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity. Bonus Adjustments Walk-Forward Validation Bonus: if (WFO_Validated): Fitness += (WFO_Efficiency - 0.5) × 0.1 Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio. Signal Efficiency Bonus (if diagnostics enabled): if (Signals_Evaluated > 10): Pass_Rate = Signals_Passed / Signals_Evaluated Fitness += (Pass_Rate - 0.1) × 0.05 Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades. Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values) Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling. 🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION This is what separates AGE from curve-fitted garbage indicators. The Three-Phase Process Every new strategy undergoes a rigorous validation lifecycle: Phase 1 - Training Window (First 250 bars, configurable 100-500): Strategy trades normally via shadow portfolio All trades count toward training performance metrics System learns which gene combinations produce profitable patterns Tracks independently: Training_Trades, Training_Wins, Training_PnL Phase 2 - Testing Window (Next 75 bars, configurable 30-200): Strategy continues trading without any parameter changes Trades now count toward testing performance metrics (separate tracking) This is out-of-sample data - strategy has never seen these bars during "optimization" Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL Phase 3 - Validation Check: Minimum_Trades = 5 (configurable 3-15) IF (Train_Trades >= Minimum AND Test_Trades >= Minimum): WR_Efficiency = Test_WinRate / Train_WinRate Expectancy_Efficiency = Test_Expectancy / Train_Expectancy WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2 IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9 Strategy.Validated = TRUE Strategy receives fitness bonus ELSE: Strategy receives 30% fitness penalty ELSE: Validation deferred (insufficient trades in one or both periods) What Validation Means Validated Strategy (Green "✓ VAL" in dashboard): Performed at least 55% as well on unseen data compared to training data Gets fitness bonus: +(efficiency - 0.5) × 0.1 Receives priority during tournament selection for breeding More likely to be chosen as active trading strategy Unvalidated Strategy (Orange "○ TRAIN" in dashboard): Failed to maintain performance on test data (likely curve-fitted to training period) Receives 30% fitness penalty (0.7x multiplier) Makes strategy prime candidate for culling Can still trade but with lower selection probability Insufficient Data (continues collecting): Hasn't completed both training and testing periods yet OR hasn't achieved minimum trade count in both periods Validation check deferred until requirements met Why 55% Efficiency Threshold? If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data. The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading. 🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time. Four Volatility Measurement Methods 1. ATR Ratio (Simple Method): Current_Vol = ATR(14) / Close Baseline_Vol = SMA(Current_Vol, 100) Ratio = Current_Vol / Baseline_Vol Basic comparison of current ATR to 100-bar moving average baseline. 2. Parkinson (High-Low Range Based): For each bar: HL = log(High / Low) Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2))) More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise. 3. Garman-Klass (OHLC Based): HL_Term = 0.5 × ² CO_Term = (2×log(2) - 1) × ² GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period) Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information. 4. Ensemble Method (Default - Median of All Three): Ratio_1 = ATR_Current / ATR_Baseline Ratio_2 = Parkinson_Current / Parkinson_Baseline Ratio_3 = GK_Current / GK_Baseline DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3) Why Ensemble? Takes median to avoid outliers and false spikes If ATR jumps but range-based methods stay calm, median prevents overreaction If one method fails, other two compensate Most robust approach across different market conditions Sensitivity Scaling Scaled_Ratio = (Raw_Ratio) ^ Sensitivity Sensitivity 0.3: Cube root - heavily dampens volatility impact Sensitivity 0.5: Square root - moderate dampening Sensitivity 0.7 (Default): Balanced response to volatility changes Sensitivity 1.0: Linear - full 1:1 volatility impact Sensitivity 1.5: Exponential - amplified response to volatility spikes Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors. How DVS Affects Shadow Trading Every strategy's stop and target distances are multiplied by the current DVS ratio: Stop Loss Distance: Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio Take Profit Distance: Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio Example Scenario: ATR = 10 points Strategy's ATR_Mult gene = 2.5 Strategy's Stop_Mult gene = 1.5 Strategy's Target_Mult gene = 2.5 DVS_Ratio = 1.4 (40% above baseline volatility - market heating up) Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol) Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol) Result: During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking Strategies adapt risk management to match current market behavior 🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL Initialization (Bar 1) AGE begins with 4 seed strategies (if evolution enabled): Seed Strategy #0 (Balanced): All sensitivities at 1.0 (neutral) Zero probability boost Moderate trend requirement (0.4) Standard ATR/stop/target multiples (2.5/1.5/2.5) Mid-level regime adaptation (0.5) Seed Strategy #1 (Momentum-Focused): Lower entropy sensitivity (0.7), higher momentum (1.5) Slight probability boost (+0.03) Higher trend requirement (0.5) Tighter stops (1.3), wider targets (3.0) Seed Strategy #2 (Entropy-Driven): Higher entropy sensitivity (1.5), lower momentum (0.8) Slight probability penalty (-0.02) More trend tolerant (0.6) Wider stops (1.8), standard targets (2.5) Seed Strategy #3 (Structure-Based): Balanced entropy/momentum (0.8/0.9), high structure (1.4) Slight probability boost (+0.02) Lower trend requirement (0.35) Moderate risk parameters (1.6/2.8) All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled. Spawning New Strategies Timing (Adaptive): Historical phase: Every 30 bars (configurable 10-100) Live phase: Every 200 bars (configurable 100-500) Automatically switches to live timing when barstate.isrealtime triggers Conditions: Current population < max population limit (default: 8, configurable 4-12) At least 2 active strategies exist (need parents) Available slot in population array Selection Process: Run tournament selection 3 times with different seeds Each tournament: randomly sample active strategies, pick highest fitness Best from 3 tournaments becomes Parent 1 Repeat independently for Parent 2 Ensures fit parents but maintains diversity Crossover Breeding: For each of 10 genes: Parent1_Fitness = fitness Parent2_Fitness = fitness Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness) Gene1 = parent1's value Gene2 = parent2's value Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2 Fitness-weighted crossover ensures fitter parent contributes more genetic material. Mutation: For each gene in child: IF (random < mutation_rate): Gene_Range = GENE_MAX - GENE_MIN Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX) Historical mutation rate: 20% (aggressive exploration) Live mutation rate: 8% (conservative stability) Mutation strength: 12% of gene range (configurable 5-25%) Initialization of New Strategy: Unique ID assigned (total_spawned counter) Parent ID recorded Generation = max(parent generations) + 1 Birth bar recorded (for age tracking) All performance metrics zeroed Shadow portfolio reset WFO validation flag set to false (must prove itself) Result: New strategy with hybrid DNA enters population, begins trading in next bar. Competition (Every Bar) All active strategies: Calculate their signal based on unique DNA Check quality gate with their thresholds Manage shadow positions (entries/exits) Update performance metrics Recalculate fitness score Track WFO validation progress Strategies compete indirectly through fitness ranking - no direct interaction. Culling Weak Strategies Timing (Adaptive): Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval) Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval) Minimum Adaptation Score (MAS): Initial MAS = 0.10 MAS decays: MAS × 0.995 every cull cycle Minimum MAS = 0.03 (floor) MAS represents the "survival threshold" - strategies below this fitness level are vulnerable. Culling Conditions (ALL must be true): Population > minimum population (default: 3, configurable 2-4) At least one strategy has fitness < MAS Strategy's age > culling interval (prevents premature culling of new strategies) Strategy is not in top N elite (default: 2, configurable 1-3) Culling Process: Find worst strategy: For each active strategy: IF (age > cull_interval): Fitness = base_fitness IF (not WFO_validated AND WFO_enabled): Fitness × 0.7 // 30% penalty for unvalidated IF (Fitness < MAS AND Fitness < worst_fitness_found): worst_strategy = this_strategy worst_fitness = Fitness IF (worst_strategy found): Count elite strategies with fitness > worst_fitness IF (elite_count >= elite_preservation_count): Deactivate worst_strategy (set active flag = false) Increment total_culled counter Elite Protection: Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak. Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time. Selection for Display (Every Bar) AGE chooses one strategy to display signals: Best fitness = -1 Selected = none For each active strategy: Fitness = base_fitness IF (WFO_validated): Fitness × 1.3 // 30% bonus for validated strategies IF (Fitness > best_fitness): best_fitness = Fitness selected_strategy = this_strategy Display selected strategy's signals on chart Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios. 🎨 PREMIUM VISUALIZATION SYSTEM AGE includes sophisticated visual feedback that standard indicators lack: 1. Gradient Probability Cloud (Optional, Default: ON) Multi-layer gradient showing signal buildup 2-3 bars before entry: Activation Conditions: Signal persistence > 0 (same directional signal held for multiple bars) Signal probability ≥ minimum threshold (65% by default) Signal hasn't yet executed (still in "forming" state) Visual Construction: 7 gradient layers by default (configurable 3-15) Each layer is a line-fill pair (top line, bottom line, filled between) Layer spacing: 0.3 to 1.0 × ATR above/below price Outer layers = faint, inner layers = bright Color transitions from base to intense based on layer position Transparency scales with probability (high prob = more opaque) Color Selection: Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong Base transparency: 92%, reduces by up to 8% for high-probability setups Dynamic Behavior: Cloud grows/shrinks as signal persistence increases/decreases Redraws every bar while signal is forming Disappears when signal executes or invalidates Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades. 2. Population Fitness Ribbon (Optional, Default: ON) Histogram showing fitness distribution across active strategies: Activation: Only draws on last bar (barstate.islast) to avoid historical clutter Visual Construction: 10 histogram layers by default (configurable 5-20) Plots 50 bars back from current bar Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action) Each layer represents a fitness threshold (evenly spaced min to max fitness) Layer Logic: For layer_num from 0 to ribbon_layers: Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers) Count strategies with fitness ≥ threshold Height = ATR × 0.15 × (count / total_active) Y_position = base_level + ATR × 0.2 × layer Color = Gradient from weak to strong based on layer position Line_width = Scaled by height (taller = thicker) Visual Feedback: Tall, bright ribbon = healthy population, many fit strategies at high fitness levels Short, dim ribbon = weak population, few strategies achieving good fitness Ribbon compression (layers close together) = population converging to similar fitness Ribbon spread = diverse fitness range, active selection pressure Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving. 3. Confidence Halo (Optional, Default: ON) Circular polyline around entry signals showing probability strength: Activation: Draws when new position opens (shadow_position changes from 0 to ±1) Visual Construction: 20-segment polyline forming approximate circle Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short) Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence) Scales with: (probability - min_probability) / (1.0 - min_probability) Color Coding: Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%) Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%) Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%) Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%) Technical Detail: Uses chart.point array with index-based positioning 5-bar horizontal spread for circular appearance (±5 bars from entry) Curved=false (Pine Script polyline limitation) Fill color matches line color but more transparent (88% vs line's transparency) Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story. 4. Evolution Event Markers (Optional, Default: ON) Visual indicators of genetic algorithm activity: Spawn Markers (Diamond, Cyan): Plots when total_spawned increases on current bar Location: bottom of chart (location.bottom) Color: theme.spawn_marker (cyan/bright blue) Size: tiny Indicates new strategy just entered population Cull Markers (X-Cross, Red): Plots when total_culled increases on current bar Location: bottom of chart (location.bottom) Color: theme.cull_marker (red/pink) Size: tiny Indicates weak strategy just removed from population What It Tells You: Frequent spawning early = population building, active exploration Frequent culling early = high selection pressure, weak strategies dying fast Balanced spawn/cull = healthy evolutionary churn No markers for long periods = stable population (evolution plateaued or optimal genes found) 5. Entry/Exit Markers Clear visual signals for selected strategy's trades: Long Entry (Triangle Up, Green): Plots when selected strategy opens long position (position changes 0 → +1) Location: below bar (location.belowbar) Color: theme.long_primary (green/cyan depending on theme) Transparency: Scales with probability: Elite (85%+): 0% (fully opaque) Strong (75-85%): 10% Good (65-75%): 20% Acceptable (55-65%): 35% Size: small Short Entry (Triangle Down, Red): Plots when selected strategy opens short position (position changes 0 → -1) Location: above bar (location.abovebar) Color: theme.short_primary (red/pink depending on theme) Transparency: Same scaling as long entries Size: small Exit (X-Cross, Orange): Plots when selected strategy closes position (position changes ±1 → 0) Location: absolute (at actual exit price if stop/target lines enabled) Color: theme.exit_color (orange/yellow depending on theme) Transparency: 0% (fully opaque) Size: tiny Result: Clean, probability-scaled markers that don't clutter chart but convey essential information. 6. Stop Loss & Take Profit Lines (Optional, Default: ON) Visual representation of shadow portfolio risk levels: Stop Loss Line: Plots when selected strategy has active position Level: shadow_stop value from selected strategy Color: theme.short_primary with 60% transparency (red/pink, subtle) Width: 2 Style: plot.style_linebr (breaks when no position) Take Profit Line: Plots when selected strategy has active position Level: shadow_target value from selected strategy Color: theme.long_primary with 60% transparency (green, subtle) Width: 2 Style: plot.style_linebr (breaks when no position) Purpose: Shows where shadow portfolio would exit for stop/target Helps visualize strategy's risk/reward ratio Useful for manual traders to set similar levels Disable for cleaner chart (recommended for presentations) 7. Dynamic Trend EMA Gradient-colored trend line that visualizes trend strength: Calculation: EMA(close, trend_length) - default 50 period (configurable 20-100) Slope calculated over 10 bars: (current_ema - ema ) / ema × 100 Color Logic: Trend_direction: Slope > 0.1% = Bullish (1) Slope < -0.1% = Bearish (-1) Otherwise = Neutral (0) Trend_strength = abs(slope) Color = Gradient between: - Neutral color (gray/purple) - Strong bullish (bright green) if direction = 1 - Strong bearish (bright red) if direction = -1 Gradient factor = trend_strength (0 to 1+ scale) Visual Behavior: Faint gray/purple = weak/no trend (choppy conditions) Light green/red = emerging trend (low strength) Bright green/red = strong trend (high conviction) Color intensity = trend strength magnitude Transparency: 50% (subtle, doesn't overpower price action) Purpose: Subconscious awareness of trend state without checking dashboard or indicators. 8. Regime Background Tinting (Subtle) Ultra-low opacity background color indicating detected market regime: Regime Detection: Efficiency = directional_movement / total_range (over trend_length bars) Vol_ratio = current_volatility / average_volatility IF (efficiency > 0.5 AND vol_ratio < 1.3): Regime = Trending (1) ELSE IF (vol_ratio > 1.5): Regime = Volatile (2) ELSE: Regime = Choppy (0) Background Colors: Trending: theme.regime_trending (dark green, 92-93% transparency) Volatile: theme.regime_volatile (dark red, 93% transparency) Choppy: No tint (normal background) Purpose: Subliminal regime awareness Helps explain why signals are/aren't generating Trending = ideal conditions for AGE Volatile = fewer signals, higher thresholds applied Choppy = mixed signals, lower confidence Important: Extremely subtle by design. Not meant to be obvious, just subconscious context. 📊 ENHANCED DASHBOARD Comprehensive real-time metrics in single organized panel (top-right position): Dashboard Structure (5 columns × 14 rows) Header Row: Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST) Column 1: "POPULATION" Column 2: "PERFORMANCE" Column 3: "CURRENT SIGNAL" Column 4: "ACTIVE STRATEGY" Column 0: Market State Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP) DVS Ratio (current volatility scaling factor, format: #.##) Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding) Trend Strength (0-100 scale, format: #.##) Column 1: Population Metrics Active strategies (count / max_population) Validated strategies (WFO passed / active total) Current generation number Total spawned (all-time strategy births) Total culled (all-time strategy deaths) Column 2: Aggregate Performance Total trades across all active strategies Aggregate win rate (%) - color-coded: Green (>55%) Orange (45-55%) Red (<45%) Total P&L in R-multiples - color-coded by positive/negative Best fitness score in population (format: #.###) MAS - Minimum Adaptation Score (cull threshold, format: #.###) Column 3: Current Signal Status Status indicator: "▲ LONG" (green) if selected strategy in long position "▼ SHORT" (red) if selected strategy in short position "⏳ FORMING" (orange) if signal persisting but not yet executed "○ WAITING" (gray) if no active signal Confidence percentage (0-100%, format: #.#%) Quality assessment: "🔥 ELITE" (cyan) for 85%+ probability "✓ STRONG" (bright green) for 75-85% "○ GOOD" (green) for 65-75% "- LOW" (dim) for <65% Confluence score (X/3 format) Signal age: "X bars" if signal forming "IN TRADE" if position active "---" if no signal Column 4: Selected Strategy Details Strategy ID number (#X format) Validation status: "✓ VAL" (green) if WFO validated "○ TRAIN" (orange) if still in training/testing phase Generation number (GX format) Personal fitness score (format: #.### with color coding) Trade count P&L and win rate (format: #.#R (##%) with color coding) Color Scheme: Panel background: theme.panel_bg (dark, low opacity) Panel headers: theme.panel_header (slightly lighter) Primary text: theme.text_primary (bright, high contrast) Secondary text: theme.text_secondary (dim, lower contrast) Positive metrics: theme.metric_positive (green) Warning metrics: theme.metric_warning (orange) Negative metrics: theme.metric_negative (red) Special markers: theme.validated_marker, theme.spawn_marker Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage Purpose: Quick overview of entire system state No need to check multiple indicators Trading decisions informed by population health, regime state, and signal quality Transparency into what AGE is thinking 🔍 DIAGNOSTICS PANEL (Optional, Default: OFF) Detailed signal quality tracking for optimization and debugging: Panel Structure (3 columns × 8 rows) Position: Bottom-right corner (doesn't interfere with main dashboard) Header Row: Column 0: "🔍 DIAGNOSTICS" Column 1: "COUNT" Column 2: "%" Metrics Tracked (for selected strategy only): Total Evaluated: Every signal that passed initial calculation (direction ≠ 0) Represents total opportunities considered ✓ Passed: Signals that passed quality gate and executed Green color coding Percentage of evaluated signals Rejection Breakdown: ⨯ Probability: Rejected because probability < minimum threshold Most common rejection reason typically ⨯ Confluence: Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed) ⨯ Trend: Rejected because signal opposed strong trend Indicates counter-trend protection working ⨯ Regime: Rejected because volatile regime detected and probability wasn't high enough to override Shows regime filter in action ⨯ Volume: Rejected because volume < 70% of 20-bar average Indicates volume confirmation requirement Color Coding: Passed count: Green (success metric) Rejection counts: Red (failure metrics) Percentages: Gray (neutral, informational) Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings. How to Use Diagnostics Scenario 1: Too Few Signals Evaluated: 200 Passed: 10 (5%) ⨯ Probability: 120 (60%) ⨯ Confluence: 40 (20%) ⨯ Others: 30 (15%) Diagnosis: Probability threshold too high for this strategy's DNA. Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA. Scenario 2: Too Many False Signals Evaluated: 200 Passed: 80 (40%) Strategy win rate: 45% Diagnosis: Quality gate too loose, letting low-quality signals through. Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree). Scenario 3: Regime-Specific Issues ⨯ Regime: 90 (45% of rejections) Diagnosis: Frequent volatile regime detection blocking otherwise good signals. Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state. Optimization Workflow: Enable diagnostics Run 200+ bars Analyze rejection patterns Adjust settings based on data Re-run and compare pass rate Disable diagnostics when satisfied ⚙️ CONFIGURATION GUIDE 🧬 Evolution Engine Settings Enable AGE Evolution (Default: ON): ON: Full genetic algorithm (recommended for best results) OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing) Max Population (4-12, Default: 8): Higher = more diversity, more exploration, slower performance Lower = faster computation, less exploration, risk of premature convergence Sweet spot: 6-8 for most use cases 4 = minimum for meaningful evolution 12 = maximum before diminishing returns Min Population (2-4, Default: 3): Safety floor - system never culls below this count Prevents population extinction during harsh selection Should be at least half of max population Elite Preservation (1-3, Default: 2): Top N performers completely immune to culling Ensures best genes always survive 1 = minimal protection, aggressive selection 2 = balanced (recommended) 3 = conservative, slower gene pool turnover Historical: Spawn Interval (10-100, Default: 30): Bars between spawning new strategies during historical data Lower = faster evolution, more exploration Higher = slower evolution, more evaluation time per strategy 30 bars = ~1-2 hours on 15min chart Historical: Cull Interval (20-200, Default: 60): Bars between culling weak strategies during historical data Should be 2x spawn interval for balanced churn Lower = aggressive selection pressure Higher = patient evaluation Live: Spawn Interval (100-500, Default: 200): Bars between spawning during live trading Much slower than historical for stability Prevents population chaos during live trading 200 bars = ~1.5 trading days on 15min chart Live: Cull Interval (200-1000, Default: 400): Bars between culling during live trading Should be 2x live spawn interval Conservative removal during live trading Historical: Mutation Rate (0.05-0.40, Default: 0.20): Probability each gene mutates during breeding (20% = 2 out of 10 genes on average) Higher = more exploration, slower convergence Lower = more exploitation, faster convergence but risk of local optima 20% balances exploration vs exploitation Live: Mutation Rate (0.02-0.20, Default: 0.08): Mutation rate during live trading Much lower for stability (don't want population to suddenly degrade) 8% = mostly inherits parent genes with small tweaks Mutation Strength (0.05-0.25, Default: 0.12): How much genes change when mutated (% of gene's total range) 0.05 = tiny nudges (fine-tuning) 0.12 = moderate jumps (recommended) 0.25 = large leaps (aggressive exploration) Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change 📈 Signal Quality Settings Min Signal Probability (0.55-0.80, Default: 0.65): Quality gate threshold - signals below this never generate 0.55-0.60 = More signals, accept lower confidence (higher risk) 0.65 = Institutional-grade balance (recommended) 0.70-0.75 = Fewer but higher-quality signals (conservative) 0.80+ = Very selective, very few signals (ultra-conservative) Min Confluence Score (1-3, Default: 2): Required indicator agreement before signal generates 1 = Any single indicator can trigger (not recommended - too many false signals) 2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance) 3 = All 3 must agree (very selective, few signals, high quality) Base Persistence Bars (1-5, Default: 2): Base bars signal must persist before entry System adapts automatically: High probability signals (75%+) enter 1 bar faster Low probability signals (<68%) need 1 bar more Trending regime: -1 bar (faster entries) Volatile regime: +1 bar (more confirmation) 1 = Immediate entry after quality gate (responsive but prone to whipsaw) 2 = Balanced confirmation (recommended) 3-5 = Patient confirmation (slower but more reliable) Cooldown After Trade (3-20, Default: 8): Bars to wait after exit before next entry allowed Prevents overtrading and revenge trading 3 = Minimal cooldown (active trading) 8 = Balanced (recommended) 15-20 = Conservative (position trading) Entropy Length (10-50, Default: 20): Lookback period for market order/disorder calculation Lower = more responsive to regime changes (noisy) Higher = more stable regime detection (laggy) 20 = works across most timeframes Momentum Length (5-30, Default: 14): Period for RSI/ROC calculations 14 = standard (RSI default) Lower = more signals, less reliable Higher = fewer signals, more reliable Structure Length (20-100, Default: 50): Lookback for support/resistance swing range 20 = short-term swings (day trading) 50 = medium-term structure (recommended) 100 = major structure (position trading) Trend EMA Length (20-100, Default: 50): EMA period for trend detection and direction bias 20 = short-term trend (responsive) 50 = medium-term trend (recommended) 100 = long-term trend (position trading) ATR Period (5-30, Default: 14): Period for volatility measurement 14 = standard ATR Lower = more responsive to vol changes Higher = smoother vol calculation 📊 Volatility Scaling (DVS) Settings Enable DVS (Default: ON): Dynamic volatility scaling for adaptive stop/target placement Highly recommended to leave ON OFF only for testing fixed-distance stops DVS Method (Default: Ensemble): ATR Ratio: Simple, fast, single-method (good for beginners) Parkinson: High-low range based (good for intraday) Garman-Klass: OHLC based (sophisticated, considers gaps) Ensemble: Median of all three (RECOMMENDED - most robust) DVS Memory (20-200, Default: 100): Lookback for baseline volatility comparison 20 = very responsive to vol changes (can overreact) 100 = balanced adaptation (recommended) 200 = slow, stable baseline (minimizes false vol signals) DVS Sensitivity (0.3-1.5, Default: 0.7): How much volatility affects scaling (power-law exponent) 0.3 = Conservative, heavily dampens vol impact (cube root) 0.5 = Moderate dampening (square root) 0.7 = Balanced response (recommended) 1.0 = Linear, full 1:1 vol response 1.5 = Aggressive, amplified response (exponential) 🔬 Walk-Forward Optimization Settings Enable WFO (Default: ON): Out-of-sample validation to prevent overfitting Highly recommended to leave ON OFF only for testing or if you want unvalidated strategies Training Window (100-500, Default: 250): Bars for in-sample optimization 100 = fast validation, less data (risky) 250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min 500 = patient validation, more data (conservative) Testing Window (30-200, Default: 75): Bars for out-of-sample validation Should be ~30% of training window 30 = minimal test (fast validation) 75 = balanced (recommended) 200 = extensive test (very conservative) Min Trades for Validation (3-15, Default: 5): Required trades in BOTH training AND testing periods 3 = minimal sample (risky, fast validation) 5 = balanced (recommended) 10+ = conservative (slow validation, high confidence) WFO Efficiency Threshold (0.3-0.9, Default: 0.55): Minimum test/train performance ratio required 0.30 = Very loose (test must be 30% as good as training) 0.55 = Balanced (recommended) - test must be 55% as good 0.70+ = Strict (test must closely match training) Higher = fewer validated strategies, lower risk of overfitting 🎨 Premium Visuals Settings Visual Theme: Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple) Carbon Fiber: Industrial look (blue/red/gray) Quantum Blue: Quantum computing (blue/purple/pink) Aurora: Northern lights (teal/orange/purple) ⚡ Gradient Probability Cloud (Default: ON): Multi-layer gradient showing signal buildup Turn OFF if chart lags or for cleaner look Cloud Gradient Layers (3-15, Default: 7): More layers = smoother gradient, more CPU intensive Fewer layers = faster, blockier appearance 🎗️ Population Fitness Ribbon (Default: ON): Histogram showing fitness distribution Turn OFF for cleaner chart Ribbon Layers (5-20, Default: 10): More layers = finer fitness detail Fewer layers = simpler histogram ⭕ Signal Confidence Halo (Default: ON): Circular indicator around entry signals Size/brightness scales with probability Minimal performance cost 🔬 Evolution Event Markers (Default: ON): Diamond (spawn) and X (cull) markers Shows genetic algorithm activity Minimal performance cost 🎯 Stop/Target Lines (Default: ON): Shows shadow portfolio stop/target levels Turn OFF for cleaner chart (recommended for screenshots/presentations) 📊 Enhanced Dashboard (Default: ON): Comprehensive metrics panel Should stay ON unless you want zero overlays 🔍 Diagnostics Panel (Default: OFF): Detailed signal rejection tracking Turn ON when optimizing settings Turn OFF during normal use (slight performance cost) 📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR Phase 1: Initial Setup & Learning Add AGE to your chart Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio) Works on: 5min (day trading), 4H (swing trading), Daily (position trading) Load 1000+ bars for sufficient evolution history Let the population evolve (100+ bars minimum) First 50 bars: Random exploration, poor results expected Bars 50-150: Population converging, fitness improving Bars 150+: Stable performance, validated strategies emerging Watch the dashboard metrics Population should grow toward max capacity Generation number should advance regularly Validated strategies counter should increase Best fitness should trend upward toward 0.50-0.70 range Observe evolution markers Diamond markers (cyan) = new strategies spawning X markers (red) = weak strategies being culled Frequent early activity = healthy evolution Activity slowing = population stabilizing Be patient. Evolution takes time. Don't judge performance before 150+ bars. Phase 2: Signal Observation Watch signals form Gradient cloud builds up 2-3 bars before entry Cloud brightness = probability strength Cloud thickness = signal persistence Check signal quality Look at confidence halo size when entry marker appears Large bright halo = elite setup (85%+) Medium halo = strong setup (75-85%) Small halo = good setup (65-75%) Verify market conditions Check trend EMA color (green = uptrend, red = downtrend, gray = choppy) Check background tint (green = trending, red = volatile, clear = choppy) Trending background + aligned signal = ideal conditions Review dashboard signal status Current Signal column shows: Status (Long/Short/Forming/Waiting) Confidence % (actual probability value) Quality assessment (Elite/Strong/Good) Confluence score (2/3 or 3/3 preferred) Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable. Phase 3: Manual Trading Execution When Long Signal Fires: Verify confidence level (dashboard or halo size) Confirm trend alignment (EMA sloping up, green color) Check regime (preferably trending or choppy, avoid volatile) Enter long manually on your broker platform Set stop loss at displayed stop line level (if lines enabled), or use your own risk management Set take profit at displayed target line level, or trail manually Monitor position - exit if X marker appears (signal reversal) When Short Signal Fires: Same verification process Confirm downtrend (EMA sloping down, red color) Enter short manually Use displayed stop/target levels or your own AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH. Phase 4: Set Up Alerts (Never Miss a Signal) Right-click on indicator name in legend Select "Add Alert" Choose condition: "AGE Long" = Long entry signal fired "AGE Short" = Short entry signal fired "AGE Exit" = Position reversal/exit signal Set notification method: Sound alert (popup on chart) Email notification Webhook to phone/trading platform Mobile app push notification Name the alert (e.g., "AGE BTCUSD 15min Long") Save alert Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts. Phase 5: Monitor Population Health Weekly Review: Check dashboard Population column: Active count should be near max (6-8 of 8) Validated count should be >50% of active Generation should be advancing (1-2 per week typical) Check dashboard Performance column: Aggregate win rate should be >50% (target: 55-65%) Total P&L should be positive (may fluctuate) Best fitness should be >0.50 (target: 0.55-0.70) MAS should be declining slowly (normal adaptation) Check Active Strategy column: Selected strategy should be validated (✓ VAL) Personal fitness should match best fitness Trade count should be accumulating Win rate should be >50% Warning Signs: Zero validated strategies after 300+ bars = settings too strict or market unsuitable Best fitness stuck <0.30 = population struggling, consider parameter adjustment No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset) Aggregate win rate <45% sustained = system not working on this instrument/timeframe Health Check Pass: 50%+ strategies validated Best fitness >0.50 Aggregate win rate >52% Regular spawn/cull activity Selected strategy validated Phase 6: Optimization (If Needed) Enable Diagnostics Panel (bottom-right) for data-driven tuning: Problem: Too Few Signals Evaluated: 200 Passed: 8 (4%) ⨯ Probability: 140 (70%) Solutions: Lower min probability: 65% → 60% or 55% Reduce min confluence: 2 → 1 Lower base persistence: 2 → 1 Increase mutation rate temporarily to explore new genes Check if regime filter is blocking signals (⨯ Regime high?) Problem: Too Many False Signals Evaluated: 200 Passed: 90 (45%) Win rate: 42% Solutions: Raise min probability: 65% → 70% or 75% Increase min confluence: 2 → 3 Raise base persistence: 2 → 3 Enable WFO if disabled (validates strategies before use) Check if volume filter is being ignored (⨯ Volume low?) Problem: Counter-Trend Losses ⨯ Trend: 5 (only 5% rejected) Losses often occur against trend Solutions: System should already filter trend opposition May need stronger trend requirement Consider only taking signals aligned with higher timeframe trend Use longer trend EMA (50 → 100) Problem: Volatile Market Whipsaws ⨯ Regime: 100 (50% rejected by volatile regime) Still getting stopped out frequently Solutions: System is correctly blocking volatile signals Losses happening because vol filter isn't strict enough Consider not trading during volatile periods (respect the regime) Or disable regime filter and accept higher risk Optimization Workflow: Enable diagnostics Run 200+ bars with current settings Analyze rejection patterns and win rate Make ONE change at a time (scientific method) Re-run 200+ bars and compare results Keep change if improvement, revert if worse Disable diagnostics when satisfied Never change multiple parameters at once - you won't know what worked. Phase 7: Multi-Instrument Deployment AGE learns independently on each chart: Recommended Strategy: Deploy AGE on 3-5 different instruments Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold) Each learns optimal strategies for that instrument's personality Take signals from all 5 charts Natural diversification reduces overall risk Why This Works: When one market is choppy, others may be trending Different instruments respond to different news/catalysts Portfolio-level win rate more stable than single-instrument Evolution explores different parameter spaces on each chart Setup: Same settings across all charts (or customize if preferred) Set alerts for all Take every validated signal across all instruments Position size based on total account (don't overleverage any single signal) ⚠️ REALISTIC EXPECTATIONS - CRITICAL READING What AGE Can Do ✅ Generate probability-weighted signals using genetic algorithms ✅ Evolve strategies in real-time through natural selection ✅ Validate strategies on out-of-sample data (walk-forward optimization) ✅ Adapt to changing market conditions automatically over time ✅ Provide comprehensive metrics on population health and signal quality ✅ Work on any instrument, any timeframe, any broker ✅ Improve over time as weak strategies are culled and fit strategies breed What AGE Cannot Do ❌ Win every trade (typical win rate: 55-65% at best) ❌ Predict the future with certainty (markets are probabilistic, not deterministic) ❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize) ❌ Guarantee profits under all market conditions ❌ Replace your trading discipline and risk management ❌ Execute trades automatically (this is an indicator, not a strategy) ❌ Prevent all losses (drawdowns are normal and expected) ❌ Adapt instantly to regime changes (re-learning takes 50-100 bars) Performance Realities Typical Performance After Evolution Stabilizes (150+ bars): Win Rate: 55-65% (excellent for trend-following systems) Profit Factor: 1.5-2.5 (realistic for validated strategies) Signal Frequency: 5-15 signals per 100 bars (quality over quantity) Drawdown Periods: 20-40% of time in equity retracement (normal trading reality) Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal) Evolution Timeline: Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet Bars 50-150: Population converging, fitness climbing - results improving Bars 150-300: Stable performance, most strategies validated - consistent results Bars 300+: Mature population, optimal genes dominant - best results Market Condition Dependency: Trending Markets: AGE excels - clear directional moves, high-probability setups Choppy Markets: AGE struggles - fewer signals generated, lower win rate Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades Market Regime Changes: When market shifts from trending to choppy overnight Validated strategies can become temporarily invalidated AGE will adapt through evolution, but not instantly Expect 50-100 bar re-learning period after major regime shifts Fitness may temporarily drop then recover This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on: Patience during learning periods (don't abandon after 3 losses) Proper position sizing (risk 0.5-2% per trade, not 10%) Following signals consistently (cherry-picking defeats statistical edge) Not abandoning system prematurely (give it 200+ bars minimum) Understanding probability (60% win rate means 40% of trades WILL lose) Respecting market conditions (trending = trade more, choppy = trade less) Managing emotions (AGE is emotionless, you need to be too) Expected Drawdowns: Single-strategy max DD: 10-20% of equity (normal) Portfolio across multiple instruments: 5-15% (diversification helps) Losing streaks: 3-5 consecutive losses expected periodically No indicator eliminates risk. AGE manages risk through: Quality gates (rejecting low-probability signals) Confluence requirements (multi-indicator confirmation) Persistence requirements (no knee-jerk reactions) Regime awareness (reduced trading in chaos) Walk-forward validation (preventing overfitting) But it cannot prevent all losses. That's inherent to trading. 🔧 TECHNICAL SPECIFICATIONS Platform: TradingView Pine Script v5 Indicator Type: Overlay indicator (plots on price chart) Execution Type: Signals only - no automatic order placement Computational Load: Moderate to High (genetic algorithms + shadow portfolios) 8 strategies × shadow portfolio simulation = significant computation Premium visuals add additional load (gradient cloud, fitness ribbon) TradingView Resource Limits (Built-in Caps): Max Bars Back: 500 (sufficient for WFO and evolution) Max Labels: 100 (plenty for entry/exit markers) Max Lines: 150 (adequate for stop/target lines) Max Boxes: 50 (not heavily used) Max Polylines: 100 (confidence halos) Recommended Chart Settings: Timeframe: 15min to 1H (optimal signal/noise balance) 5min: Works but noisier, more signals 4H/Daily: Works but fewer signals Bars Loaded: 1000+ (ensures sufficient evolution history) Replay Mode: Excellent for testing without risk Performance Optimization Tips: Disable gradient cloud if chart lags (most CPU intensive visual) Disable fitness ribbon if still laggy Reduce cloud layers from 7 to 3 Reduce ribbon layers from 10 to 5 Turn off diagnostics panel unless actively tuning Close other heavy indicators to free resources Browser/Platform Compatibility: Works on all modern browsers (Chrome, Firefox, Safari, Edge) Mobile app supported (full functionality on phone/tablet) Desktop app supported (best performance) Web version supported (may be slower on older computers) Data Requirements: Real-time or delayed data both work No special data feeds required Works with TradingView's standard data Historical + live data seamlessly integrated 🎓 THEORETICAL FOUNDATIONS AGE synthesizes advanced concepts from multiple disciplines: Evolutionary Computation Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor Tournament Selection: Fitness-based parent selection with diversity preservation Crossover Operators: Fitness-weighted gene recombination from two parents Mutation Operators: Random gene perturbation for exploration of new parameter space Elitism: Preservation of top N performers to prevent loss of best solutions Adaptive Parameters: Different mutation rates for historical vs. live phases Technical Analysis Support/Resistance: Price structure within swing ranges Trend Following: EMA-based directional bias Momentum Analysis: RSI, ROC, MACD composite indicators Volatility Analysis: ATR-based risk scaling Volume Confirmation: Trade activity validation Information Theory Shannon Entropy (1948): Quantification of market order vs. disorder Signal-to-Noise Ratio: Directional information vs. random walk Information Content: How much "information" a price move contains Statistics & Probability Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization Out-of-Sample Validation: Testing on unseen data to prevent overfitting Monte Carlo Principles: Shadow portfolio simulation with realistic execution Expectancy Theory: Win rate × avg win - loss rate × avg loss Probability Distributions: Signal confidence quantification Risk Management ATR-Based Stops: Volatility-normalized risk per trade Volatility Regime Detection: Market state classification (trending/choppy/volatile) Drawdown Control: Peak-to-trough equity measurement R-Multiple Normalization: Performance measurement in risk units Machine Learning Concepts Online Learning: Continuous adaptation as new data arrives Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown) Exploration vs. Exploitation: Balance between trying new strategies and using proven ones Overfitting Prevention: Walk-forward validation as regularization Novel Contribution: AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation. Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself. The combination of: Genetic algorithm population management Shadow portfolio simulation for realistic fitness evaluation Walk-forward validation to prevent overfitting Multi-indicator confluence for signal quality Dynamic volatility scaling for adaptive risk ...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches. 🏗️ DEVELOPMENT NOTES This project represents months of intensive development, facing significant technical challenges: Challenge 1: Making Genetics Actually Work Early versions spawned garbage strategies that polluted the gene pool: Random gene combinations produced nonsensical parameter sets Weak strategies survived too long, dragging down population No clear convergence toward optimal solutions Solution: Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown) Elite preservation (top 2 always protected) Walk-forward validation (unproven strategies penalized 30%) Tournament selection (fitness-weighted breeding) Adaptive culling (MAS decay creates increasing selection pressure) Challenge 2: Balancing Evolution Speed vs. Stability Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes. Solution: Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals) Adaptive mutation rates: 20% historical, 8% live Spawn/cull ratio: Always 2:1 to prevent population collapse Challenge 3: Shadow Portfolio Accuracy Needed realistic trade simulation without lookahead bias: Can't peek at future bars for exits Must track multiple portfolios simultaneously Stop/target checks must use bar's high/low correctly Solution: Entry on close (realistic) Exit checks on current bar's high/low (realistic) Independent position tracking per strategy Cooldown periods to prevent unrealistic rapid re-entry ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes Challenge 4: Pine Script Compilation Limits Hit TradingView's execution limits multiple times: Too many array operations Too many variables Too complex conditional logic Solution: Optimized data structures (single DNA array instead of 8 separate arrays) Minimal visual overlays (only essential plots) Efficient fitness calculations (vectorized where possible) Strategic use of barstate.islast to minimize dashboard updates Challenge 5: Walk-Forward Implementation Standard WFO is difficult in Pine Script: Can't easily "roll forward" through historical data Can't re-optimize strategies mid-stream Must work in real-time streaming environment Solution: Age-based phase detection (first 250 bars = training, next 75 = testing) Separate metric tracking for train vs. test Efficiency calculation at fixed interval (after test period completes) Validation flag persists for strategy lifetime Challenge 6: Signal Quality Control Early versions generated too many signals with poor win rates: Single indicators produced excessive noise No trend alignment No regime awareness Instant entries on single-bar spikes Solution: Three-layer confluence system (entropy + momentum + structure) Minimum 2-of-3 agreement requirement Trend alignment checks (penalty for counter-trend) Regime-based probability adjustments Persistence requirements (signals must hold multiple bars) Volume confirmation Quality gate (probability + confluence thresholds) The Result A system that: Truly evolves (not just parameter sweeps) Truly validates (out-of-sample testing) Truly adapts (ongoing competition and breeding) Stays within TradingView's platform constraints Provides institutional-quality signals Maintains transparency (full metrics dashboard) Development time: 3+ months of iterative refinement Lines of code: ~1500 (highly optimized) Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL Test timeframes: 5min, 15min, 1H, Daily 🎯 FINAL WORDS The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool. This is evolution in action on your charts. You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation. AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime. Use it on any instrument. Any timeframe. Any market condition. AGE will adapt. This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much . Trust the process. Respect the evolution. Let Darwin work. "In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change." Taking you to school. — Dskyz, Trade with insight. Trade with anticipation. — Happy Holiday's
Индикатор Pine Script®
от DskyzInvestments
3
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy? The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions. Here's how it functions: Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time. Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate. Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends. Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider: Specifically, it considers: Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income. Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation. GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy. Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors. By integrating these elements, the strategy aims to: Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings. Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time. Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions. ---- What are Regular Contributions in this strategy? Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate. ---- How do regular contributions enhance compounding and reduce timing risk? Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time. Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility. Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success. ---- How does the strategy integrate technical and fundamental analysis for investors? A: The strategy combines technical and fundamental analysis in the following manner: Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s). Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential. This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets. ---- How does the strategy identify market structure? What are the underlying calculations? Q: How does the strategy identify market structure? A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed. What are the underlying calculations for identifying market structure? A: The underlying calculations involve: Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it. Break of Structure (BOS): Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend. Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend. Structural Liquidity and Invalidation: Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS. Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend. This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages. By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool. What entry criteria are used in this script? The script uses two entry models for trading decisions: BreakOut and Fractal. Underlying Calculations: Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade. Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern. ---- How does the script calculate trend score? What are the underlying calculations? Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves: Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis). Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low. Percentage-Based Score: This ratio is then converted into a percentage-based score: For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength. The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100. User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level. Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe. This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements. What type of stop-loss identification method are used in this strategy? This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss. Underlying Calculations: Initial Stop-loss: ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction. Calculation: - First, the True Range (TR) is calculated for each period, which is the greatest of: - Current Period High - Current Period Low - Absolute Value of Current Period High - Previous Period Close - Absolute Value of Current Period Low - Previous Period Close - The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility. Swing Low Based: For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss. Trailing Stop-Loss: The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves: Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement. Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses. By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably. Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels. Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns. What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations? For Break-Even: Percentage (%) Based: Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry. Calculation: Break-even level = Entry Price * (1 + Percentage / 100) Example: If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105. Risk-to-Reward (RR) Based: Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio. Calculation: Break-even level = Entry Price + (Initial Risk * RR Ratio) For TP - You can choose to set a take profit level at which your position gets fully closed. - Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR. What's the day filter Filter, what does it do? The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style. Customize Session Time: Users can define the start and end times for the trading session. This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours. Select Days: Users can select which days of the week to include in the strategy. This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays). Benefits: Focus on Optimal Trading Periods: By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities. Avoid Unfavorable Conditions: Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays. What tables are available in this script? - Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more. Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart. Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability. Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit. MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position. Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses. Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit. Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control. BE Trades: Number of break-even trades, excluding commission/slippage. Losing Trades: The total number of losing trades generated by the strategy. Winning Trades: The total number of winning trades generated by the strategy. Total Trades: Total number of taken traders visible your charts. Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign. - Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year. - Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations. - UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S. User-input styles and customizations: Please note that all background colors in the style are disabled by default to enhance visualization. How to Use This Strategy to Create a Profitable Edge and Systems? Choose Your Strategy mode: - Decide whether you are creating an investing strategy or a trading strategy. Select a Market: - Choose a one-sided market such as stocks, indices, or cryptocurrencies. Historical Data: - Ensure the historical data covers at least 10 years of price action for robust backtesting. Timeframe Selection: - Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits. Set Commission and Slippage: - Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications. Parameter Optimization: - Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester. Trade Count: - Ensure the number of trades is 200 or more; the higher, the better for statistical significance. Positive Average Trade: - Make sure the average trade is above zero. (An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.) Performance Metrics: - Look for a high profit factor, and net profit with minimum drawdown. - Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance. Refinement and Optimization: - Try out different markets and timeframes. - Continue working on refining your edge using the available filters and components to further optimize your strategy. What makes this strategy original? Incorporation of Fundamental Analysis: This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time. Technical Analysis Without Classical Methods: The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system. Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits: Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes. Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals. Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals. Regular Contributions and Reminders: The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach: Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time. Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility. Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success. Long-Term Wealth Building: Focused on long-term wealth accumulation, this strategy: Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations. Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure. Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades. This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time. Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited. - By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Стратегия Pine Script®
от Fractalyst
1
Chartology Strategy+🔍 Chartology Strategy+ This tool provides a comprehensive way for users to analyze trend levels and access other Matrix features across selected tickers and timeframes. Results can be tailored by strategy, with the option to filter displayed tickers based on custom user‑defined rules. Bullish & Bearish Entry Signal (Safe & Scalping). Entry Level, SL, T-SL & Two TP Levels (Based on Possible Movement). Dashboard Table for Easy Presentation of All Levels. Timeframe Scanner for Current Signal (Trend) on Different Timeframes. Gap Up & Gap Down for Untraded Price Marking. Institutional Candles for High Volume and Big Price Movement. Neutral Candle for Low Volume and Small Price Movement. Supply Demand (Based on Swing High & Low). Mega Trend Band (Based on HMA) for Overall Trend. 🟢 Bullish & Bearish Entry Signals Shows the expected direction of the symbol. It shows Bullish and Bearish direction mark on Chart. Entry Level is Closing of the Candle. Input Settings Signal Type: Safe Appears after a proper trend confirmation. Low frequency, fewer signals, but more reliable. Best for swing traders who want strong confirmation before entering. Signal Type: Scalping Appears frequently during small downward moves. High frequency, quick signals for short-term trades. Best for intraday Traders who want multiple opportunities in small movements. 🎯 Entry Level, SL, T-SL & TP Levels Generated based on price movement and trend range. Levels on Chart Entry Level: Closing price of the candle where the signal appears. SL (Stop Loss): Maximum risk allowed for the trade. TSL (Trailing SL): Dynamic SL to reduce risk and lock profits. Level 01: First TP level with 1:1 risk-reward ratio. Used for partial booking. Level 02: Final TP level for full exit. Input Settings Levels: You can Increase or Decrease Level Amount for the Level 2. Risk: You can Increase or Decrease Stop Loss (SL). 📊 Dashboard Table for Easy Presentation of All Levels. Displays all key levels and metrics in one place: Metrics Symbol Name Shows the name of the current chart (e.g., NIFTY, BANKNIFTY). Bar Age Displays the How many candles (Bars) before Latest signal appears. Entry Shows the entry level where the latest bullish or bearish signal was generated. Level 1 (TP1) First target level, based on 1:1 risk-reward ratio. Used for partial booking to secure profits. Level 2 (TP2) Final target level where you can exit the remaining position. SL (Stop Loss) Shows the maximum risk limit for the trade. Helps you control losses. MTM (Mark to Market) Shows the difference between CMP and Entry Level. Helps track how far price has moved since entry. P&L (Profit & Loss) Shows the difference between Entry and Target Level achieved. Helps measure actual gain or loss. Date & Time Displays when the latest bullish or bearish signal was generated. Helps check how old or fresh the signal is. Timeframe Scanner or Current Signal (Trend) on Different Timeframes. Shows the current signal across multiple timeframes. Row 1 Fixed signals for 1M and 3M. Row 2 Any 2 Custom Timeframes chosen in input settings. Traders use this to confirm signals across different timeframes before entering trades. Example If the Day trend is bullish but the 15M chart shows bearish, many traders avoid that trade. 🚦 Gap Up & Gap Down for Untraded Price Marking. Marks untraded price zones where price may react. Gap Up & Down Flag Mark Gap Up: Bullish Bias, Marked Green flag, plotted when candle opens above previous high. Gap Down: Bearish Bias, Marked as Red flag, plotted when candle opens below previous low. Input Settings Enable / Disable from Chart Threshold: Minimum gap size Threshold to detect 🟡 Institutional Candles for High Volume and Big Price Movement Indicate strong price movement with high volume. Marking Displayed as Yellow Body Candles Helps identify zones where big players are active. Input Settings Enable / Disable from Chart Body %: Compare of Open & Close with High & Low Size %: Compare Total Candle Size from Past Range Volume %: Compare Total Candle Volume from Past Range ⚪ Neutral Candle for Low Volume and Small Price Movement Shows low volume and minimal price movement. Marking Displayed as Hollow Body Candles Traders usually avoid trading during these candles. Input Settings Enable / Disable from Chart. Candle %: Compare Size of candles. Volume %: Compare Volume of Candles from Previous Range. 🟥🟩 Supply Demand Zones (Based on Swing High & Low). Based on swing highs and lows to identify possible reversals. Zones 🟥Supply Zone: Near swing high, marked with Light Red Zone. 🟩Demand Zone: Near swing low, marked with Light Green Zone. Input Settings: Bars Left: How many past Bars Swing will Calculate. Bars Right: After How many Bars, Zone will plot. Max Zones: Number of Supply or Demand Zone want to plot on Chart Delete Breaked Zones: Want to see Disappeared Zone, Uncheck it. Extend Right: Want to see till End of the Chart, Uncheck it. 📈 Mega Trend Band (Based on HMA) for Overall Trend Based on HMA (Hull Moving Average) to show overall trend and Help in Filters out trades against the main trend. Working Price above band → Bullish trend Price below band → Bearish trend Input Setting Enable / Disable from Chart HMA Period Setting: 45 👓 How to Use All together for Better Confidence. 🔍Watch for the New Entry icon on the chart. Find New Signals with help of Automated Alerts. Check Entry Level, SL, Level 1 and Level 2 (TP2). Verify Date & Time → how fresh the signal is. Signal not too old. 🧭 Signal is not Self Sufficient for Good Accuracy. So, we suggest a few rules. Cross‑Check Current Signal with Timeframe Scanner. Trade only when smaller timeframe aligns with bigger trend. (e.g., If Day = Bullish ▲ but 15M = Bearish ▼, avoid entry. Trend may not be stronger.) Validate with Market Context of Gap. (e.g., If new signal came on Gap Up / Gap Down, avoid entry. Price may reverse.) Zone Awareness Use Supply Demand zones to refine entries/exits and avoid false signals. (e.g., Entry: If any zone is available between Entry and Level 01, Avoid trade until Zone breaked, Exit: If Zone create between the trade, modify SL according to T-SL and wait. Trend Filter of overall direction. (e.g., If Mega Trend Band Bullish and Trend is Bearish, Avoid the Trade.) 🕵🏻 Quick Checklist Before Trade Bullish or Bearish signal? Dashboard Table shows fresh entry? SL defined and acceptable risk? Timeframe Scanner aligned? No Neutral candle interference? Institutional candle or Gap supports move? Supply/Demand zone not against trade? ✅ All Okay - Go for the ENTRY Set a Proper Entry Point Always respect SL, Good Trader Never avoid it. Book partial profits at Level 1, It secure your Trade. Keep Modifying your SL, According to T-SL Level. On Level 2, Exit remaining All position for full profit. 📊 Healthy Trading Tips Risk Small: Never risk more than 1–2% per trade. Size Smart: Adjust position size to volatility and account size. Diversify: Don’t put all money in one asset/sector. Plan Ahead: Set entry, exit, and stop‑loss before trading. Trade Less: Focus on quality setups, avoid overtrading. Use Both Analyses: Combine technical charts with fundamental news/events. Control Emotions: Stick to strategy, avoid fear/greed. Journal Trades: Record reasons, outcomes, and lessons. Stay Informed: Track economic calendars and global events. Take Breaks: Step away after wins/losses to reset. 🎯 Advanced Discipline Partial Exit: Book profits in stages (e.g., 50% at 1:1, 50% at Final Level). Check News: Avoid trading during major announcements. No Tweaks: Don’t change plan mid‑trade; wait for SL/TP. Fixed Rules: Trade with fixed risk, fixed gains. No Averaging Losses: Close bad trades, don’t add more. Keep Learning: Evolve strategy with market changes. Believe: Trust your plan and process. Backtest: Practice setups until they’re second nature. Daily Routine: Pre‑market Preparation, post‑market review. Optimize Setup: Clean workspace, fast platform, no distractions. Track Metrics: Win rate, average reward, expectancy, time of day, setup performance. Trader Identity: Follow rules; money is a byproduct. Liquidity Check: Avoid low‑volume instruments. Respect Trend: Trade with momentum, not against it. Avoid Over‑Leverage: Keep leverage low, avoid margin unless planned. Risk Disclaimer This content, including any tools, software, datafeeds, indicators, or scanners, is provided strictly for charting, educational, informational, and paper‑trading purposes only. It does not constitute investment advice, buy/sell recommendations, or real‑money trading strategies. Not Advisors: We are not registered as investment advisors or research analysts. Charting Only: Use is limited to testing strategies and evaluation; any application to real trading is at the user’s sole risk. No Liability: No liability is accepted for financial loss, trading loss, or damages arising from use of the tools or data. Data Limitations: Market data may be delayed, inaccurate, or incomplete. Past or hypothetical performance is not indicative of future results. Signals Disclaimer: Automated signals are for evaluation only and should not be treated as accurate or real trading instructions. High Risk: Trading and investing involve substantial risk and can result in losses beyond the initial capital. Independent Judgment: Users must exercise independent judgment and consult licensed professionals before making financial decisions ⚠️ Final Note: Trading is speculative and may not be suitable for all investors. Use only risk capital and never invest money you cannot afford to lose. ✅ Always remember🧠 my 3R Rule💡: If the money💰 is yours then, RISK⚖️, REWARD🏆 and REGRET😔 are solely yours. 🔥
Индикатор Pine Script®
от Chartology-AI
Easy Trade Pro [Buy and Sell Strategy + Backtesting System]Hello Traders, Easy Trade Pro is a comprehensive tool that combines multiple technical indicators into a single customizable one. This tool is the culmination of an extensive trading career, it is designed to help traders navigate the markets in any timeframe and financial asset, like Equities, Futures, Crypto, Forex and Commodities. Before we deep dive into the comprehensive guide on what Easy Trade Pro is, let's kick off by showcasing the strategy used in this example. Please note, we have adopted an extremely conservative approach strictly following the Tradingview House Rules, which you can review here: www.tradingview.com The backtest strategy parameters: Currency pair: EUR USD Timeframe: 15-min chart Market: Spot, no leverage Broker: FXCM Trading range: 2022-09-01 07:30 — 2023-06-26 20:00 Backtesting range: 2022-08-31 23:00 — 2023-06-26 20:00 Initial Capital: $10,000 Buy Order Size: 20% of the capital, $2,000 Stop Loss: 0.50% Sell orders: Four different take profits where we unload the position by 25% each time Broker Fees: Commission set at 0.08$ Slippage: 10 ticks Understanding FXCM Commissions and Setting Realistic Slippage for EUR/USD Spot Trading: ◉I would like to provide some clarity on the commission structure and slippage setting used in the study for trading the EUR/USD pair on the FXCM spot market. Based on the information available, FXCM charges a commission of $4.00 per standard lot (100,000) on both sides of the trade (meaning at open and close) for the EUR/USD pair. Since the study involve an order size of $2,000 USD, which is equivalent to 0.02 lots, the commission fee for one side of the trade (either buying or selling) would be calculated as $4.00 multiplied by 0.02, which is $0.08. This means that for each individual trade, whether it be a buy or sell, the commission fee would be $0.08. ◉As for slippage, it is crucial to account for the inherent uncertainty in the execution price due to market fluctuations. In the forex market, the EUR/USD pair is quoted with a precision of five decimal places, with the smallest price change being a "pipette" (0.00001). Given that slippage can vary based on market conditions, it is considered fair practice to use a slippage of around 10 ticks under normal market conditions for the EUR/USD pair. This allows for a more realistic representation of the execution price, especially in a liquid and fast-moving market such as forex. More detailed information about FXCM fees structure in the link below: docs.fxcorporate.com Enter a Trade conditions: For our buy order, we utilize a custom buy signal called 'Bullish Reversal'. A detailed explanation of this and other buy orders can be found later in the guide, specifically in section 1). To enhance realism in our trading strategy, we have implemented a confirmation mechanism. When utilizing the strategy tester, you have the option to input a value to determine the number of confirmation candles to consider. For example, if you set the input to 1, the system will check if the next candle following the signal meets the criteria for confirmation. If set to 2, the system will evaluate the second candle, and so on for higher values. The confirmation is determined by comparing the closing or opening price of the selected buy signal candle with the corresponding closing price of the confirmation candle. In this case we choose as buy signal: 'Bullish Reversal' + 2 candle of confirmation Exit a trade conditions: On the sell side, we exit a trade in four different types of sell orders where we take profits. Inside '', you will encounter unique labels attributed to our custom sell signals. A detailed explanation of these sell orders can be found later in the guide, specifically in section 1). We used custom order called: 1TP 'Good Sell' 2TP 'Good Sell' 3TP 'Good Sell' 4TP 'Bearish Reversal' + 4 confirmation candles Our confirmation logic, for sell signals, is applied only to 'Bearish Reversal' signal. The confirmation is determined by comparing the closing or opening price of the selected 'Bearish Reversal' candle with the corresponding closing price of the confirmation candle. In this case, we wait for the fourth candle from the 'Bearish Reversal' signal to confirm the sell trade. Protect your capital: This super-conservative study involves a clear low risk, with the use of $2,000, 20% of our capital. If the stop loss of 0.5% were triggered, we lose 10$, equating to 0.10% of $10,000 - thus affecting only 0.10% of our capital. Super Conservative Approach & Results: With 353 closed trades, we achieved a net profit of 2.03%, or $203.34$ relative to our initial $10,000 capital, and a win rate of 73.37%. Less Conservative Approach & Results: We could also consider increasing our risk to 0.5% of our capital per trade. We would maintain our stop loss at 0.50%, but we would need to use all our capital to enter the market. If the stop loss of 0.5% will be triggered, we would lose 50$, equating to 0.5% of $10,000. In this scenario, our net profit would have increased to 10.15%, equivalent to $1015. Please be aware: While fully automated strategies can bring considerable advantages, they are not without their cons. For one, relying solely on an automated system may not take into account the potential confluence of other strategies or indicators, such as the significance of support and resistance zones. These elements often require a more nuanced, human understanding of the markets and cannot always be perfectly replicated by an algorithm. Additionally, it's essential to remember that a significant percentage of traders are not consistently profitable. As such, prudent risk management, a conservative approach, and acceptance of a reasonable profit are crucial aspects of successful trading. While the allure of high returns can be tempting, the sustainability of your trading strategy should always take precedence. Achieving steady, reliable profits over time often outweighs the appeal of a risky, high-return strategy that could potentially lead to substantial losses. So, while automation can be a powerful tool in your trading arsenal, it's also important to consider other strategies and factors. Always ensure you're managing your risk effectively and approaching trading with a realistic and informed perspective. ------------------------------------------------------------------------ Why Easy Trade Pro is Original? ---------------------------------------------------------------------------------- We developed Easy Trade Pro as a unique and comprehensive solution, and we decided to protect our code to preserve its originality. We invested significant time and effort into making it a realistic trading strategy simulator. The standout features that set Easy Trade Pro apart include: ☀ Versatile Stop Loss Mechanisms: Stop loss execution can be complex and often requires careful coding to work as intended. In most freely available open-source codes, stop losses are implemented using the Average True Range (ATR). ATR can be beneficial but has limitations: ☁ Lagging Indicator - Like most technical indicators, the ATR is a lagging indicator. This means it is based on past data, and so it may not accurately reflect future market volatility. If market conditions change rapidly, the ATR may not adjust quickly enough, potentially leading to suboptimal stop loss levels. ☁ No Directional Information - The ATR measures volatility, but it does not provide any indication of the direction of the trend. Therefore, it should not be used as a standalone tool for making trading decisions, but should be used in conjunction with other technical analysis tools that can provide directional cues. ☁ Inefficiency in Trending Markets - In strongly trending markets, ATR-based stops can sometimes be too far from the current price level. This could lead to larger losses if the price moves against your trade before hitting the stop loss. On the flip side, in less volatile, sideways markets, an ATR-based stop might be set too close to the entry point, leading to premature stop outs. ☁ Overoptimization Risk - If you're backtesting a trading strategy, there's a risk of overoptimizing your stop loss settings by fine-tuning them to past data. The best ATR multiplier that worked in the past might not necessarily work in the future, leading to potential performance issues. ☀ We countered these by implementing four different types of 'protect the trade' mechanisms: ✔ Fixed Percentage Stop Loss ✔ Trailing Stop Loss ✔ Stop Loss Moved to Entry Upon Reaching Certain Gain ✔ Stop Loss Moved to Entry Upon Reaching First Take Profit Order ("Custom Order"). ☀ Dual Exit Strategy: We incorporated two distinct methods of exiting a trade. The first uses our custom signals, while the second triggers exit at a certain percentage of gain. ☀ Multiple Take Profit Orders: You have the flexibility to establish up to four different sell orders. This feature enables you to fractionate your exit strategy according to your needs. You can choose to trigger these fractions based on our custom signals or determine your own exit points by setting targeted gains at a fixed percentage. ☀ Confirmation Candle System: This feature enhances trade precision by requiring confirmation candles after a buy or sell signal. This confirmation, dependent on the next candle's closing price, helps reduce false signals and improves entry and exit points. While our confirmation system is applicable to all custom buy signals, it's solely dedicated for the bearish reversal when it comes to sell signals. ☀ Universal Compatibility: Easy Trade Pro's Strategy Tester works perfectly with any asset class. The code can handle different contract types, including the SPX contracts and fractional assets like Bitcoin. It's optimized to ensure proper execution of trades without rounding issues. ☀ Bullish and Bearish Reversal candles: Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations. ☀ Non-Repainting Indicator: Our indicator signals are designed not to repaint. Once a signal appears, it stays fixed, offering a reliable tool for your trading decisions. ================================================== EXTENSIVE TECHNICAL DESCRIPTION ==================================================== Easy Trade Pro is versatile, allowing you to analyze market trends across any financial asset. With its rigorous testing, our tool can be used confidently on any timeframe, from 1D to 1min, whether you prefer longer-term or shorter-term trades. Although we recommend trading on timeframes between 1D and 1min, higher timeframes like 1W chart, can also provide broader insights. Our study combines a variety of popular technical indicators, such as RSI, Stochastic RSI, MACD, DMI, Bollinger Bands as well as relevant EMAs. On the volume side OBV and MFI. Using a data-driven approach, “Easy Trade Pro” analyzes historical market trends to identify optimal ways to combine these indicators with significant divergences between price and oscillators. On top of that the code considers relevant changes in market structure and liquidity grabs, to generate reliable and accurate signals for potential buy and sell opportunities. * ☎ --> Please not that MACD, BBs, and EMAs account for a minimal part of our script <--- ☎, If you're looking for a simpler tool, consider checking out our open-source indicator, 'RSI, SRSI, MACD, and DMI cross - Open source code'. You can find it here: With our customizable system, traders will be able to identify: 1) Three types of buy signals🐂,💰,💎 and sell signals 🐻,🔨,💀 2) Bullish and bearish reversal candles with support and resistance lines 3) Bull and bear momentum signals 4) A function that utilizes Color bars to identify the strength of the trend 5) Three customizable moving averages 6) Alerts direct to your email or phone 7) Advanced and customizable settings menu 8) Our software also includes a backtesting system that that allows users to test their trading strategies on historical data, to check how they would have performed in real-world market conditions. This can help refine a trading strategy and make more informed decisions. ------------------------------------------------------------------------------ 1) BUY AND SELL SIGNALS --------------------------------------------------------------------------------- Our buy and sell signals are generated using a custom combination of RSI, MFI, and Stochastic RSI levels, as well as relevant MACD and Stochastic RSI crosses. These indicators are carefully analyzed to identify potential trading opportunities and determine optimal entry and exit points for trades. RSI (Relative strength index) measures the strength of a security's price action, while the SRSI (Stochastic Relative Strength Index) is a momentum oscillator that measures the current price relative to its high and low range over a set period. The Money Flow Index (MFI) is another momentum indicator that uses both price and volume data to measure buying and selling pressure. MACD (Moving Average Convergence Divergence) is a popular technical indicator used in financial markets to analyze price trends and momentum. ▶ With our system, you'll be able to identify three different levels of buy signals: ◉ The first level of buy signal is represented by a 🐂 emoji and is a "Good Buy". This signal indicates a possible buying opportunity. It indicates that could be a good opportunity to enter in a long trade. It's important to note that, the "Good Buy" signal can sometimes be supplemented with a green "Bull" text and a flag plotshape positioned beneath the signal. In these scenarios, we categorize this as a "Good Buy Bull" signal. ◉ The second level of buy signal is represented by a 💰 emoji and is a "Great Buy". This signal indicates a stronger buying opportunity than the "Good Buy" signal. ◉ The third and strongest buy signal is represented by a 💎 emoji and is an "Incredible Buy". This signal indicates a stronger buying opportunity than the "Good Buy" and "Great Buy" signals ▶ With our system, you'll be able to identify three different levels of sell signals: ◉ On the sell side, the first level is represented by a 🐻 emoji and is a "Good Sell". This signal indicates a possible selling opportunity. It indicates that could be a good opportunity to exit a trade or open a short position. It's important to note that, the "Good Sell" signal can occasionally be accompanied by a red "Bear" text and a flag plotshape positioned beneath the signal. In such instances, we refer to this as a "Good Sell Bear" signal. ◉ The second sell signal is represented by a 🔨 emoji and is a "Great Sell". This signal indicates a stronger selling opportunity than the "Good Sell" signal. ◉ The third and strongest sell signal is represented by a 💀 emoji and is an "Incredible Sell". This signal indicates a stronger selling opportunity than the "Good Sell" and "Great Sell" signals. ------------------------------------------2) "BULLISH AND BEARISH REVERSAL CANDLES PLUS SUPPORT AND RESISTANCE LINES" ------------------------------------------------ Bullish and bearish reversal candles are specific candles that have more probability to reverse the trend. Our trading indicator is designed to identify bullish and bearish reversal candles. Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations. These candles are represented by blue and orange colors respectively by default. Additionally, the indicator also uses lines that are drawn at either the opening or closing of candles to help identify pivot points of support or resistance. These candles, lines color or shape are customizable in the settings menu. How can I benefit the most from bullish reversal candles? To make the most of bullish reversal candles, a powerful strategy is: E.g, 1D chart - Wait for the next 1 or 2 candles to close above the support line linked to the bullish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. A good tip is also to look for other signals (confluence), like a buy signal. Traders should decide based on their risk tolerance. Here below we can see an example of a bullish reversal candle in the BTC/USDT, 1D, chart. The system identify a bullish reversal candle (blue color), the next 2 candles are green and closed above the support blue line, in addition we have other bullish signals (confluence). How can I benefit the most from bullish reversal lines? Bullish reversal lines can help traders to identify key level of support and maintain control of their position until a clear break below occurs. In the example below we se how the price retrace to the support line: After touching the price bounce up. How can I benefit the most from bearish reversal candles? To make the most of bearish reversal candles, a powerful strategy is: E.g, 1D chart - Wait for the next 1 or 2 candles to close below the resistance line linked to the bearish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. Traders should decide based on their risk tolerance. Here below we can see an example of a bearish reversal candle in the ETH/USDT, 1D, chart. The system identify a bearish reversal candle (orange color), the next candle is red and closes below the resistance orange line. A good tip is also to look for other signals (confluence), like a sell signal. How can I benefit the most from bearish reversal lines? Bearish reversal lines can help traders to identify key level of resistance and maintain control of their position until a clear break above occurs. In the example below we se how the price bounce back to the resistance line and get rejected. ------------------------------------------------------------------------- 3) BULL AND BEAR MOMENTUM SIGNALS ----------------------------------------------------------------------- We analyzed factors such as buy or sell signals, long or short confirmation signals, DMI crossup or crossdown and breaks of market structure (BOS) or change of character (CHoCh) to determine the strength and direction of the trend. These study give us bull trend or bear trend signals that can help traders identify potential trading opportunities and make informed decisions. These conditions are represented by a green word "BULL" and a flag shape below (bull momentum) and by a red word "BEAR" and a flag shape above (bear momentum) respectively by default. These plots shapes are customizable in the settings menu. How can I benefit the most from bull momentum signals? To make the most of bull momentum signals, a powerful strategy is: E.g, 1D chart - Look for confluence. If bull signal comes with a "Good Buy 🐂" in the same candle the signal is more strong. Another good combo is to look for a bullish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision. In the picture below we can see an example of a bull momentum signal in the US500, 1D, chart. How can I benefit the most from bear momentum signals? To make the most of bear momentum signals, a powerful strategy is: E.g, 1D chart - Look for confluence. If bear signal comes with a "Good Sell 🐻" in the same candle the signal is more strong. Another good combo is to look for a bearish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision. In the picture below we can see an example of a bear momentum signal in combo with a sell signal, NETFLIX, 1D, chart. -------------------------------------------------------------- 4) "COLOR BARS THAT INDICATE THE STRENGTH OF THE TREND ----------------------------------------------------- This code is responsible for changing the color of the bars on a chart based on certain conditions. The gradient colors are defined for green and red, and the algorithm checks if the current bar is within a certain range of either a bearish reversal or bullish reversal candle and whether the price is above or below certain exponential moving averages or if important break of market structure occurs. Ultimately, this feature helps traders visually identify potential trends and market shifts and avoid getting distracted by price fluctuations. Please note that every gradient of color can be customize by the user. We set 3 different bullish colors and 3 different bearish colors. Below the picture of the settings menu related to the bar color. ----------------------------------------------------------------------5)THREE CUSTOMIZABLE MOVING AVERAGES ---------------------------------------------------------------------- You can choose up to three moving averages, any length and any type like SMA, EMA, WMA, HMA, RMA, SWMA and VWMA. Furthermore, you have the freedom to adjust the color and width of the lines to your preference. Below the picture of the settings menu related to the moving averages. ----------------------------------------------------------------------6) ALERTS DIRECT TO YOUR EMAIL OR PHONE -------------------------------------------------------------------- Our alert feature sends real-time notifications directly to your email or phone when a signal is generated, allowing you to take immediate action and stay ahead of the market. With our system, you first establish your own rules for trading in the strategy tester - this includes your criteria for entering and exiting trades. Once you've defined these conditions, our system will start sending you alerts. These alerts will be triggered whenever your specified conditions are met. So, if the market matches your 'enter trade' conditions, you'll receive an alert prompting. Similarly, when your 'exit trade' conditions are met, you'll receive another alert. Remember, these alerts are purely based on the conditions you set. Once the condition is met, you will receive alerts directly to your email or phone when enter and exit a trade based on your custom conditions. To make sure you receive these notifications click on notifications tab. ---------------------------------------------------------------7) ADVANCED AND CUSTOMIZABLE SETTINGS MENU---------------------------------------------------------------------- We designed Easy Trade indicators with traders in mind, so it's user-friendly, easy to navigate and users can customize inputs, style, and colors of every feature in the indicator's settings menu. -----------------------------------------------------------------------8) EASY TRADE PRO - BACKTESTING SYSTEM---------------------------------------------------------------------- Easy Trade Pro features a highly effective and realistic backtesting system, designed to mirror as closely as possible the real-world scenarios of entering and exiting trades. Step 1: Open the settings menu of the Indicator. Once opened the settings menu click on properties. Decide on the capital you wish to invest. Choose whether to use contracts or USD and determine the size of your orders. For the sake of realism, we recommend not exceeding 25% of your capital per order. However, if you decide to utilize your entire capital, make sure to adjust your stop loss accordingly. For instance, if you have a capital of 10K and use 10K with a stop loss at 2%, your potential loss would be $200. Conversely, if you use only 2K of your 10K capital with a stop loss at 10%, you would still lose the same 2% of your capital. To make your simulation even more authentic, consider incorporating broker fees or commissions into your calculations. For example, spot market fees are typically around 0.10%. If you're backtesting markets with low liquidity, consider factoring in slippage as well. Step 2: Navigate to the 'Inputs' section and scroll down until you come across 'Backtesting System - Strategy Test'. Once you locate this, click on the box and activate the 'USE STRATEGY SYSTEM' option by checking the tick box. Also You will then need to set a 'Start Date' and 'End Date', establishing a specific time period during which you wish to test your strategy. Otherwise you can consider to use the deep backtesting feature. Step 3: It's now time to establish the conditions for entering a trade. You can choose from five different types of custom buy signals: Good Buy, Good Buy Bull, Great Buy, Incredible Buy, and Bullish Reversal. Note that 'Great Buy' and 'Incredible Buy' are rare signals, so we advise against using them frequently in mechanical strategy tests; instead, consider them more for manual live tests. For more consistent results, we recommend using the other buy signals. After determining your preferred buy signal, you can choose how many confirmation candles you wish to wait for before entering a trade. A 'confirmation' means that if the next candle closes above the opening or closing price of the chosen buy signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (close > open) or red. You can set the number of confirmation candles in different time frames: below 2h, between 2h and 10h, and above 10h. Step 4: It's now time to safeguard your trade by managing risk. You can choose to implement a stop loss, expressed in percentage terms, or opt for a trailing stop. A trailing stop is a type of stop loss order that moves with the market price. It is designed to protect gains by enabling a trade to remain open and continue to profit as long as the market price is moving in a favorable direction. However, the trade closes if the market price changes direction by a specified amount (the 'trailing stop distance'). Additionally, you can minimize losses and move the stop loss to your entry point once the price reaches a certain percentage of profit. This strategy can help secure potential gains while limiting the potential for losses. Step 5: Now it's time to set the conditions for exiting the trade. You have the option to divide your exit into a maximum of four parts, with each part representing 25% of the position size. For each take profit point, you can choose from three different custom sell signals: Good Sell, Good Sell Bear, and Bearish Reversal. Similarly, the concept of confirmation candles also applies here, but in this case, the candles are not closing above. A 'confirmation' for a sell signal means that if the next candle closes below the opening or closing price of the selected sell signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (open > close) or red (close < open). So, when you're looking to sell, a confirmation would occur if the next candlestick's closing price is lower than the opening or closing price of the candlestick that triggered the sell signal. This indicates a potential bearish trend, providing the confirmation to execute the sell order. Additionally, we've introduced a feature that allows you to move your stop loss to the entry point whenever the first take profit (1TP) is reached, which equates to hitting one custom sell signal. Step 6: We've also designed an alternative method for taking profits. With this approach, you can choose to exit your position once a fixed percentage gain from the entry point is reached. For instance, you might decide to exit when a 10% profit is achieved. Similarly to the previous method, this approach allows you to choose up to four exit points and determine the proportion of your position you want to close at each stage. Conclusion: Easy Trade Pro provides users with various options for entering and exiting trades. To effectively utilize the indicator, we strongly recommend conducting thorough backtesting and considering the results across your preferred trading pairs. It is advisable to analyze a substantial number of trades, ideally exceeding 100 trades, to obtain reliable insights into the indicator's performance. This approach will help you gain a better understanding of how Easy Trade Pro aligns with your trading strategy and objectives. ❗Keep attention❗ It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions. It is also important to be aware of the limitations of simulated performance results. Hypothetical or simulated results do not represent actual trading, and since trades have not been executed, results may be over- or under-compensated for market factors such as lack of liquidity. Simulated trading programs are also designed with the benefit of hindsight, and no representation is being made that any account will achieve profits or losses similar to those shown. Therefore, our indicators are for informative purposes only and not intended to be used as financial advice. We encourage traders to use our indicators as part of a well-rounded trading strategy and to always be aware of the risks involved in trading. Remember that past performance is not indicative of future results and always trade responsibly.
Стратегия Pine Script®
от Trading_Paradise
6
[3Commas] Alligator StrategyThe Alligator Strategy 🔷 What it does: This script implements the Alligator Strategy, a trend-following method created by Bill Williams. It uses three customizable moving averages (SMMAs or RMAs) "Jaws," "Teeth," and "Lips" to identify market trends and potential trade opportunities. Additionally, it includes built-in stop-loss and take-profit options for enhanced risk management. 🔷 Who is it for: Trend Traders: Those who prefer trading in markets with clear directional movement. Advanced Users: Traders who require customizable tools and dynamic risk management features. Beginners: Accessible to those new to trading, thanks to its intuitive visual representation of trends and pre-configured settings. Bot Users: Supports direct signal integration for bot automation, including entries, take-profits, and stop-losses. 🔷 How does it work: The Alligator Jaws, Teeth, and Lips are smoothed moving averages (SMA, EMA, RMA, or WMA) calculated based on the selected source price ( hl2 = (high+low)/2 by default). Their lengths and offsets are customizable: Jaws: Length 21 , offset 13. Teeth: Length 13, offset 8. Lips: Length 8 , offset 5. When the lines align and spread apart (e.g., Lips > Teeth > Jaws for an uptrend), the strategy identifies a trending market. Entry Conditions: Long Trades: Triggered when Close > Lips > Teeth > Jaws. Short Trades: Triggered when Close < Lips < Teeth < Jaws. 🔷 Why it’s unique: Customization: Flexible settings for moving average types and lengths to adapt to different market conditions and strategy tester configurations. Built-in Filters: Trend filters that can reduce false signals in certain scenarios, making it more reliable for trending markets. Take Profit and Stop Loss: Configurable as either percentage-based or dynamic. Stop-loss levels adjust dynamically using the Alligator lines. Fast exit logic moves the stop-loss closer to the price when trades are in profit. 3Commas Bot Compatibility: Designed for automated trading, allowing traders to configure and execute the strategy seamlessly. 🔷 Considerations Before Using the Indicator 🔸Why the Forward Offset: By shifting the averages forward, the Alligator helps traders focus on established trends while filtering out short-term market noise. The standard configurations of 13-8, 8-5, and 5-3 were selected based on Bill Williams’ studies of market behavior. However, these values can be adjusted to suit different market conditions: Volatile Markets: Faster settings (e.g., 10-6, 6-4, 3-2) may provide earlier signals. Less Volatile Markets: Slower settings (e.g., 21-13, 13-8, 8-5) can help avoid noise and reduce false signals. 🔸Best Timeframes to Use: The Alligator can be applied across all timeframes, but certain timeframes offer better reliability. Higher Timeframes (H4, D1, W1): Ideal for identifying significant trends and for swing or position trading. Lower Timeframes: Not recommended due to increased noise but may work for scalping with additional confirmation tools. 🔸Disadvantages of the Alligator Strategy: Exhausted Entry Levels: High buying levels or low selling levels can lead to momentum exhaustion and potential pullbacks. False Signals in Ranges: Consolidating markets can produce unreliable signals. Lagging Indicator: As it is based on moving averages, it may delay reacting to sudden price changes. 🔸Advantages of the Alligator Strategy: Trend Focused: Simplifies the identification of trending markets. Noise Reduction: Forward shifts and smoothed averages help filter out short-term price fluctuations. Broad Applicability: Suitable for forex, crypto, stocks, and commodities. 🔸Important Considerations: While the Alligator Strategy provides a systematic way to analyze markets, it does not guarantee successful outcomes. Results in trading depend on multiple factors, including market conditions, trader discipline, and risk management. Past performance of the strategy does not ensure future success, and traders should always approach the market with caution. Risk Management: Define stop-loss levels, position size, and profit targets before entering any trade. Be prepared for the possibility of losses and ensure that your approach aligns with your overall trading plan. 🔷 STRATEGY PROPERTIES Symbol: BINANCE:BTCUSDT (Spot). Timeframe: 1D (Daily Timeframe). Test Period: All historical data available. Initial Capital: 10000 USDT. Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach. Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy. Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level. Margin for Long and Short Positions: 100%. Indicator Settings: Default Configuration. Alligator: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5. Strategy: Long & Short. Max Stop Loss per Trade: 10% of Trade Size. Exit trades on opposite signal: Enable. Alligator Stop Loss: Enable. Alligator Fast Exit: Enable. 🔷 STRATEGY RESULTS ⚠️ Remember, past results do not guarantee future performance. Net Profit: +355.68 USDT (+3.56%). Total Closed Trades: 103. Percent Profitable: 47.57%. Profit Factor: 1.927. Max Drawdown: -57.99 USDT (-0.56%). Average Trade: +3.45 USDT (+3.41%). Average # Bars in Trades: 16. 🔷 HOW TO USE 🔸Adjust the Alligator Settings: The default values generally work well: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5. However, if you want to use it on timeframes smaller than 4H (4 hours), consider increasing the values to better filter market noise. Please review the "Indicator Settings" section for configuration. 🔸Choose a Symbol that Typically Trends: Select an asset that tends to create trends. However, the Strategy Tester results may display poor performance, making it less suitable for sending signals to bots. 🔸Add Trend Filters: You can enable trend filters like MA and SuperTrend. By default, these are disabled as they are often unnecessary, but you can experiment with their configuration to see if they optimize the strategy's results. Please review the "Indicator Settings" section for configuration. 🔸Enable Stop Loss Levels: Activate Stop Loss features, such as Stop Loss % or Alligator Stop Loss. If both are enabled, the one closest to the price during the trade will be applied. Please review the "Indicator Settings" section for configuration. 🔸Enable Take Profit Levels: Activate Take Profit options, such as Take Profit % or Alligator Fast Exit. If both are enabled, the one that triggers first will be executed. Please review the "Indicator Settings" section for configuration. This is an example with the default settings and how Alligator Stop Loss and Alligator Fast Exit are activated: In this example, we additionally enable the Take Profit at 10%. We can observe that the Alligator Stop Loss is the active one since it is closer to the price. When the price moves 10% in favor or against the trade, the position is closed. Although the Alligator Fast Exit is enabled, it does not activate because the trades are closed beforehand. 🔸Results Review: It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed. Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic. If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds. 🔸Create alerts to trigger the DCA Bot Verify Messages: Ensure the message matches the one specified by the DCA Bot. Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format. Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured in 3Commas. Alert Setup: When creating an alert, set the condition to the indicator and choose "alert() function call only. Enter any desired Alert Name. Open the Notifications tab, enable Webhook URL, and paste the Webhook URL from 3Commas. For more details, refer to the 3Commas section: "How to use TradingView Custom Signals. Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format to 3Commas. 🔷 INDICATOR SETTINGS 🔸Alligator Settings MA's source: Source price for Alligator moving averages. MA's Type: Type of calculation for MA's. Jaw and Offset: Jaw length and offset to the right. Teeth and Offset: Teethlength and offset to the right. Lips and Offset: Lips length and offset to the right. 🔸Alligator Style Plot Alligator: Show Alligator Ribbon. Plot MA's: Show Alligator MA's. Colors: Main and Gradient Colors for Bullish Alligator, Berish Alligator, Neutral Alligator. For gradient colors it is recommended to use an opacity of 15. 🔸MA & SuperTrend Filters MA & Plot: Activate MA Filter and Plot MA on the chart. Long Entries: When activated, it will only execute entries if the price is above the MA Short Entries: When activated, it will only execute entries if the price is below the MA. Source: Source price for moving average calculations. Length: Candles to be used by the MA calculations. Type: Type of calculation for MA. Timeframe: Here you can select a larger timeframe for the filter. ST & Plot: Activate SuperTrend Filter and Plot SuperTrend on the chart. Long Entries: When activated, it will only execute entries if the price is above the SuperTrend. Short Entries: When activated, it will only execute entries if the price is below the SuperTrend. Source: Source price for SuperTrend calculations. Length: Candles to be used by the SuperTrend calculations. Factor: ATR multiplier of the SuperTrend. Timeframe: Here you can select a larger timeframe for the filter. 🔸Strategy Tester Strategy: Order Type direction in which trades are executed. Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level. Stop Loss %: When activated, the entered value will be used as the Stop Loss in percentage from the entry price level. If Alligator Stop Loss is activated, the closest one to the price will be used. Exit trades on opposite signal: This option closes the trade if the opposite condition is met. For instance, if we are in a long position and a sell signal is triggered, the long position will be closed, and a short position will be opened. The same applies inversely. Alligator Stop Loss: In a long trade, the lower part of the Alligator indicator will be used as a dynamic stop loss. Similarly, in a short trade, the upper part of the indicator will be used. Alligator Fast Exit: Its purpose is to attempt to protect movements in favor of the trade's direction. In the case of long trades, once the price and the upper part of the Alligator indicator are above the trade's entry price, the stop loss will be moved to the upper part. For short trades, once the price and the lower part of the Alligator indicator are below the trade's entry price, the stop loss will be moved to the lower part of the Alligator indicator. Alligator Squeeze Entry: When activated, entries will only be executed if they meet the condition after a neutral zone of the Alligator indicator. Alligator Squeeze Exit: When this option is activated, any open trades will be closed when the Alligator indicator enters a neutral mode. Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart. Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze. 🔸3Commas DCA Bot Signals Check Messages: Enable the table to review the messages to be sent to the bot. Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals to 3Commas. Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade. DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the 3Commas format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot. 🔷 CONCLUSION The Alligator Strategy is a valuable tool for identifying potential trends and improving decision-making. However, no trading strategy is foolproof. Careful consideration of market conditions, proper risk management, and personal trading goals are essential. Use the Alligator as part of a broader trading system, and remember that consistent learning and discipline are key to success in trading. 👨🏻‍💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented. ____________________________________________________________________ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Стратегия Pine Script®
от 3Commas
4
PSE, Practical Strategy EnginePSE, Practical Strategy Engine A ready-to-use engine that is simple to connect your indicator to, simple to use, and effective at generating alerts for order-filled events during the real-time candle. Great for • Evaluating indicators on important metrics without the need to write a strategy script for backtesting. • Using indicators with built-in risk management. About The PSE This engine accepts entry and exit signals from your indicator to provide trade signals for both long and short positions. The PSE was written for trading Funds (e.g. ETF’s), Stocks, Forex, Futures, and Cryptocurrencies. The trades on the chart indicate market, limit, and stop orders. The PSE allows for backtesting of trades along with metrics of performance based on trade-groups with many great features. Note: A link to a video of how to connect your indicator(s) to the PSE is provided below. Key Features Trade-Grp’s A Trade-Grp makes up one or more trade positions from the first position entering to the last position exiting. Using Trade-Grp’s instead of positions should help you better assess if the metric results fit your trading style. Below are two (2) examples of a Trade-Grp with three (3) positions. Metrics A table of metrics is available if the “Show Metrics Table” checkbox is enabled on the Inputs tab, but metrics always show in the Data Window. Examples of the Metrics Table are shown below. • ROI (Return on Investment) and CAGR (Compound Annual Growth Rate) are based on the Avg Invest/Trade-Grp and are adjusted for dividends if the “Include Dividends in Profit” checkbox is enabled. • Profit/Risked is based on Trade-Grp’s. Also known as reward/risk, as well as expectancy per amount risked. It determines the effectiveness of your strategy and provides a measure of comparison between your strategies. This is adjusted for dividends if the “Include Dividends in Profit” checkbox is enabled. In the Data Window the color is green when above the breakeven point of making a profit and red when below the breakeven point. In the Table the color is red if below the breakeven point, otherwise it is the default color. For example, using the 3 metrics tables above: For every USD risked the profit is 1.709 USD. For every BTC risked the profit is 0.832 BTC. For every JPY risked the profit is 0.261 JPY. • Winning % is based on Trade-Grp’s. In the Data Window the color is green when above the breakeven point of making a profit and red when below the breakeven point. In the Table the color is red if below the breakeven point, otherwise it is the default color. The breakeven point is a relationship between the Profit/Risked and Winning % to indicate system profitability potential. Another way to assess trading system performance. For example, for a low Winning % a high Profit/Risked is needed for the system to be potentially profitable. • Profit Factor (PF) is based on Trade-Grp’s. The dividend payment, if any, is not considered in the calculation of a win or loss. The “Include Dividends in Profit Factor” checkbox allows you the option to either include or not include dividends in the calculation of Profit Factor. The default is enabled. Must enable the “Include Dividends in Profit” checkbox to include dividends in PF. Including dividends in PF evaluates the trading strategy with a more overall profitability performance view. Enable/Disable “Include Dividends in Profit Factor” checkbox also affects the Avg Trade-Grp Loss, and thus Equity Loss from ECL and % Equity Loss from ECL. • Max Consecutive Losses are based on Trade-Grp’s. • Nbr of Trade-Grp’s and Nbr of Positions. These help you to determine if enough trades have occurred to validate your strategy. The Nbr of Positions is the count of positions on the chart. The TV list of trades in the Strategy Tester may indicate more than what is actually shown on the chart. The Data Window includes 'Nbr Strat Tester Trades', which equals the TV listing trades, to help you locate specific trades on the chart. • Time in Market (%) is based on Trade-Grp’s and date range selected. • Avg Invest/Trade-Grp will indicate the average amount of money invested in a Trade-Grp. This is adjusted for dividends if the “Include Dividends in Profit” checkbox is enabled. • Equivalent Consecutive Losses, labeled as Equiv. Cons. Losses (ECL). This value is determined by the Winning % and Nbr of Trade-Grp’s. This simulates the more likely case of a series of losses, then a small win, then another series of losses to form an equivalent consecutive losing streak. To lower the value, increase the Winning %. • Equity Loss from ECL is the equity loss from the equivalent consecutive losses. • % Equity Loss from ECL is the percent of equity loss from the equivalent consecutive losses. Risk Management • Pyramid rules enforce and maintain position sizing designated by you on the Inputs tab (% Equity to Risk, Up/Dwn Gap) & Properties tab (number of pyramids, slippage, and commission). A pyramid position will not occur unless both its stop covers the last entry price with gap/slippage and commission cost of previous trade is covered. If take profit is enabled, a pyramid position will not occur unless commission cost of the trade is covered when take profit target is reached. • Position sizing, stop-loss (SL), trailing stop-loss (TSL), and take profit (TP) are used. • Wash sale prevention for applicable assets is enforced. Wash sale assets include stock and fund (e.g. ETF’s). • No more than one entry position per candle is enforced . Other Great Features • Losing Trade-Grp’s indicated at the exit with label text in the color blue. Used to easily find consecutive losses affecting your strategy’s performance. The dividend payment, if any, is not considered in the calculation of a win or loss. • Position values can be displayed on the chart. The number format is based on the min tick value, but is limited to 8 decimal places only for display purposes. • Dividends per share and the amount can be displayed on the chart. • Hold Days . This is the number of days to hold before allowing the next Trade-Grp. Can be a decimal number. This feature may help those trading on a cash account to avoid any settlement violations when trading the same asset. • Date Filter. Partition the time when trading is allowed to see if the strategy works well across the date range selected. The metrics should be acceptable across all four (4) time ranges: entire range, 1st half, IQR (inter-quartile range), and 2nd half. • Price gap amount identification. Used in determining if a pyramid entry may be profitable, and may be used in determining slippage amount to use. • When TP is enabled, the PSE will only allow a pyramid position if the potential is profitable based on commission and price gap selected. • Trade-Grp’s shown in background color: green for long positions and red for short positions. • The PSE will alert you to update your stop-loss as the market changes if your exchange/broker does not allow for trailing stop-loss orders. Enable this option on the Inputs tab with Alert Chg TSL. • The PSE will alert you if your drawdown exceeds Max % Equity Drawdown set on the Inputs tab. • The PSE will send an alert to warn you of an expiring GTC order. Some brokers will indicate the order is GTC, Good 'Till Cancelled, but there really is a time limit on the order and is typically 60-120 days. Therefore, the PSE will alert you if you've been in position for close to 60 days so you can refresh your order. The alert is typically a few days before the 60-day time period. • For order fill alerts just use a {{placeholder}} in the Message of the alert. Details on how to enter placeholders is explained below. • Identify same bar enter/exit for first entries and pyramids. This is shown in the Data Window as well. This can help you determine what stop-loss % works best for your trading style. • Leverage trading information is displayed in the Data Window and applies to Trade-Grps. Failed PosSize or Margin (%): Shows a zero if the failed-to-trade position size was less than 1 or shows the margin % which failed to meet the margin requirement set in the Properties tab. A flag will show on the bar where a failed-to-trade occurred. This is only applicable to the first position of a Trade-Grp. Position the cursor over the flag for the value to show in the Data Window. Notional Value: total Trade-Grp position size x latest entry price x point value. The equity must be > notional value x margin requirement for a trade to occur. Current Margin (%): must be greater than margin requirement set on the Properties tab in order for a trade to occur. Margin Call Price: when enabled on the Style tab is displayed on both the chart and the Data Window as shown below. PSE Settings Pyramids • Pyramiding requires the Stop Method to be set to either TSL or Both (meaning SL & TSL). • The maximum number of pyramids is determined by the value entered in the Properties tab. • Pyramid orders require the enter price to be higher than the previous close for Longs and lower than the previous close for Shorts. • Pyramids also require the stop with gap/slippage to be higher than the last entry price for Longs, and lower than the last entry price for Shorts. This covers all previous positions and maintains position sizing. • When take profit, TP, is enabled, the pyramids also require that they will be profitable when opening a position assuming they will reach TP. This is automatically adjusted by you with the Dwn Gap/Up Gap, Slippage, and Commission settings. Inputs Tab General Settings Color Traded Background Enable to change background color where in a trade. Green for long positions and red for short positions. Show Losing Trade-Grp Enable to show if losing Trade-Grp and is indicated by text in blue color. The last position may be at a loss, but if there was profit for the Trade-Grp, then it will not be shown as a loss . Show Position Values Enable to show the currency value of each position in gold color. Include Dividends in Profit This feature is only applicable if the asset pays dividends and the time frame period of the chart is 1D or less, otherwise ignored. The PSE assumes dividends are taken as cash and not reinvested. Enable to adjust ROI, CAGR, Profit/Risked, Avg Invest/Trade-Grp, and Equity to include dividend payments. This feature considers if you were in position at least one day prior to the ex-dividend date and had not exited until after the ex-dividend date. When Show Dividends is enabled it will display the payout in currency/share, as well as the total amount based on the number of shares the position(s) of the Trade-Grp are currently holding. Include Dividends in Profit Factor This checkbox allows you the option to either include or not include dividends in the calculation of Profit Factor. Must enable the “Include Dividends in Profit” checkbox to include dividends in PF. The dividend payment, if any, is not considered in the calculation of a win or loss. Show Metrics Table Options are font size and table location. Alert Failed to Trade Enable for the strategy to alert you when a trade did not happen due to low equity or low order size. Applicable only for the first position of a Trade-Grp. Trade Direction Options are 'Longs Only', 'Both', 'Shorts Only'. Hold Days This is the number of days to hold before allowing the next Trade-Grp. Applies only to the first trade position of a Trade-Grp. Where a Trade-Grp consists of the first position plus any pyramid positions. The value entered will be overwritten to >= 31 to prevent wash sale for applicable assets in the event the last Trade-Grp was a loss. Wash sale assets include stock and fund (i.e. ETF’s). The minimum value is the equivalent of 1 candle and is automatically assigned by the PSE if the entered value is equivalent to less than one candle. To calculate Hold Days in # of candles on the Hour chart divide the chart period by 24 x #candles. On the Minute chart divide the chart period by 60 then by 24 x #candles. Show Vertical Lines at From Date & To Date Shows a vertical dotted line at the From Date and To Date for visual inspection of the setting. Date Filter When enabled, trades are allowed between the From Date and To Date, i.e., the date range. When disabled, trades are allowed for all candles. Partition the time when trading is allowed to see if your indicator settings work well across the date range. Click 1st Half, IQR (inter-quartile range), or 2nd Half buttons to trade a portion of the date range. Select only one at-a-time to partition the time when trading is allowed. When 1st Half is enabled only trades for the 1st half of the date range are allowed. When IQR is enabled only trades for the inter-quartile date range are allowed. When 2nd Half is enabled only trades for the 2nd half of the date range are allowed. Position Sizing The % of Equity to Risk has been separated into two (2) areas: for initial trades and for pyramid trades. This allows for greater ability to maximize profits within your acceptable drawdown. A variation of the Anti-Martingale method from the initial trade if you choose to use it in that manner. % Equity to Risk for Initial Trades: enter the percent of equity you want to risk per position for the initial trades of each Trade-Grp. For example, for 1% enter 1. % Equity to Risk for Pyramid Trades: enter the percent of equity you want to risk per position for the pyramid trades of each Trade-Grp. For example, for 2% enter 2. % Equity for Max Position Size: the position size will not exceed this amount. For example, for 25% enter 25. Max % Equity Drawdown Warning: an alert will be triggered if the maximum drawdown exceeds this v alue. For example, for 10% enter 10. Stop Methods NOTE: The Stop Method must be either Both or TSL in order for the pyramids to work. This feature enforces position sizing. Stop-loss, SL, and trailing stop-loss, TSL, are other features that enforce risk management. The trailing stop-loss, TSL, is activated immediately if Stop Method = TSL. If Stop Method = Both, then the TSL is activated when its value is above stop-loss, SL, for Longs and below the SL for Shorts. The calculated TSL value (shown on the chart by + symbol) of the previous bar is used for the current bar and the plot value is off by default, but you can it turn on via the Style tab. This is available so you can better understand how the TSL value used was calculated from. It is beneficial to show when monitoring the real-time candle. Alert Chg TSL When enabled, this feature will alert you to update your stop price if it moves greater than the change amount in %. The amount is the absolute % so will work for both Longs and Shorts. For example, for 1% enter 1 . This is provided since some exchanges/brokers do not offer TSL orders and you must manually adjust as price action plays out. The alert will also suggest a stop limit price based on the gap selected and explained below. The alert will occur at the close of the candle at the calculated TSL value of the candle just prior to the real-time candle. Dwn Gap/Up Gap Input Settings A price gap is the difference between the closing price of the previous candle and the opening price of the current candle. Dwn Gap and Up Gap are illustrated here. The values of the Dwn Gap and Up Gap can be seen in the Data Window and are based on the settings of the Date Filter. The options are “zero gap”, "median gap", "avg gap", "80 pct gap", "90 pct gap". The X pct gap stands for X percentile rank. For example, "80 pct gap" means that 80% of the gaps are less than or equal to the value shown in the Data Window. Select “zero gap” to disable this feature. If Show Stop Limit is enabled, it will show a dotted-line below or above the current stop price where a stop-limit order should be taken. It is shown based on the gap option selected. Again, the PSE trades market, limit, and stop orders, but a stop-limit may be shown if you wanted to see where one would be set using the Up/Dwn Gap. Dwn Gap: Affects Short Take Profit, Long Pyramid Entries, and to show the Long Stop Limit. Up Gap : Affects Long Take Profit, Short Pyramid Entries, and to show the Short Stop Limit. Fixed Take Profit (TP) When take profit (TP) is enabled, the PSE will determine if opening a pyramid position will be in profit assuming the TP will be hit while considering commission costs (on Properties tab). The larger of Up Gap or Slippage value is used with Long positions regarding TP. The larger of Dwn Gap or Slippage value is used with Short positions regarding TP. Properties Tab • Initial Capital: Set as desired. • Base Currency: Leave as Default. The PSE is designed to use the instrument’s currency, therefore leave as Default. • Order Size: Leave as default. This setting has been disabled and position sizing is handled on the Inputs tab and is based on % of equity. • Pyramiding: Set as desired. • Commission: Set as number %. The PSE is designed to only work with commission as a percent of the position value. • Verify Price for Limit Orders: Set as desired. Slippage Adjust Slippage on the Properties tab to account for a realistic bid-ask spread. You can use one of Dwn/Up Gap values or other guidelines. Again, the Dwn/Up Gap values are based on the Date Filter input settings. Heed warnings from the TradingView Pine Script™ manual about values entered into the Slippage field. The Slippage (ticks) have a noticeable influence on entry price and exit price especially at the beginning when the date range includes prices from $0.01 to $100,000.00 like that for BTC-USD INDEX. When this is the case, it is best to use different slippage values when partitioning time with the Date Filter. To minimize the effects of slippage, yet account for it select ‘median gap’ on the Input Tab and use that value for slippage on the Properties tab. The slippage value is included in the placeholder {{strategy.order.price}}. Leverage Trading The PSE is designed to be used both without leverage (the default) and with leverage. These two settings apply to Trade-Grps. For example, for 5x leverage enter 20 (1/5x100=20). Margin for Long Positions: Set as desired. The default is 100%. Margin for Short Positions: Set as desired. The default is 100%. This setting on the Inputs tab applies to each trade position within a Trade-Grp. Max % Equity per Position: Set as desired. The default is 20% and intended for non-leverage trading. For leverage trading set as desired. For example, for 3x leverage enter 300 (3x100=300). Recalculate After Order Is Filled The PSE uses the strategy parameter calc_on_order_fills=true to allow for enter/exit on the same bar and generate alerts immediately after an order is filled. This parameter is on the Properties tab and is named ‘Recalculate After order is filled’ and is enabled by default. Disabling this feature will cause the PSE to not work as intended. You will see the following Caution! on the TV Strategy Tester This occurs because the PSE has the strategy parameter calc_on_order_fills = true. Again, the PSE will only work as intended if this parameter is enabled and set to true. Therefore, you can close the caution sign and be confident of receiving realistic results. Recalculate On every tick: Disable. Fill Orders • Using bar magnifier: Set as desired. • On Bar Close: Disable. The PSE will not work as intended if this is enabled. • Using Standard OHLC: Set as desired. Using The Alert Message Box From TV Strategy Alert Set alerts to gain access to all the alerts from PSE. This allows for both order filled alerts, as well as the alert function calls related to refresh GTC orders, drawdown exceeded, update stop-loss order, and Failed to Trade. Example Message for Manual Trading Alerts (This is just an example. Consult TV manual for possible placeholders to use.) { Alert for {{plot("position_for_alert")}} position. (long = 1; short = -1) {{exchange}}:{{ticker}} on TF of {{interval}} at Broker Name {{strategy.order.action}} Equity x Equity_Multiplier USD in shares at price = {{strategy.order.price}}, where Equity_Multiplier = {{strategy.order.contracts}} x {{strategy.order.price}} / {{plot("Equity")}} or {{strategy.order.action}} {{strategy.order.contracts}} shares at price = {{strategy.order.price}}. } Note: Use the Equity x Equity_Multiplier method if you have several accounts with different initial capital. Example Message for Bot Trading Alerts (You must consult your specific bot for configuring the alert message. This is just an example.) { "action": "{{strategy.order.action}}", “price”: {{strategy.order.price}} "amount": {{strategy.order.contracts}}, "botId": "1234" } Connecting to the PSE The diagram below illustrates how to connect indicators to the PSE. The Aroon and MACD indicators are only used here as an example. Substitute your own indicators and add as many as you like. Connection Indicator for the PSE A video of how to connect your indicator(s) to the PSE is below. The Connection Indicator for the PSE, also called here the connection-indicator. Below is a description of how to connect your chosen indicators to the connection-indicator. Two (2) indicators were chosen for the example, but you may have one (1) or many indicators. If you have source code access to your indicators you can paste the code directly into the connection-indicator to eliminate the need to have those indicators on the chart and the additional connection of them to the connection-indicator. Below will assume source code to the indicators are not available. The MACD and Aroon Oscillator are from TV built standard indicators and are shown here just as an example for inputs (i.e. source) to the connection-indicator. They were configured as follows: The source code for the connection-indicator is shown below. Substitute your own chosen indicators and add as many as you like to create your connection-indicator that feeds into the PSE. The MACD and Aroon Oscillator were simply chosen as an example. Configure your connection-indicator in the manner shown below. // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // This is just an example Indicator to show how to interface with the PSE. // The indicators used in the example are standard TV built indicators. //@version=5 indicator(title="Connection Indicator for the PSE", overlay=false, max_lines_count=500, max_labels_count=500, max_boxes_count=500) // Ind_1 INDICATOR ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ // This is just and example and used MACD histogram as the source. Filter_Ind_1 = input.bool(false, 'Ind_1', group='Ind_1 INDICATOR ~~~~~~~~~~~~~~~~~', tooltip='Click ON to enable the indicator') input_Ind_1 = input.source(title = "input_Ind_1", defval = close, group='Ind_1 INDICATOR ~~~~~~~~~~~~~~~~~') Entry_Ind_1_Long = Filter_Ind_1 ? input_Ind_1 > 0 ? 1 : 0 : 0 Entry_Ind_1_Short = Filter_Ind_1 ? input_Ind_1 < 0 ? 1 : 0 : 0 Exit_Ind_1_Long = Entry_Ind_1_Short Exit_Ind_1_Short = Entry_Ind_1_Long // Ind_2 INDICATOR ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ // This is just an example and used Aroon Oscillator as the source. Included limits to use with the oscillator to determine enter and exit. Filter_Ind_2 = input.bool(false, "Ind_2", group='Ind_2 INDICATOR ~~~~~~~~~~~~~~', tooltip='Click ON to enable the indicator') Filter_Ind_2_Limit = input.int(35, minval=0, step=5, group='Ind_2 INDICATOR ~~~~~~~~~~~~~~') Filter_Ind_2_UL = Filter_Ind_2_Limit Filter_Ind_2_LL = -Filter_Ind_2_Limit up = input.source(title = "input_Ind_2A Up", defval = close, group='Ind_2 INDICATOR ~~~~~~~~~~~~~~') down = input.source(title = "input_Ind_2B Down", defval = close, group='Ind_2 INDICATOR ~~~~~~~~~~~~~~') oscillator = up - down Entry_Ind_2_Long = Filter_Ind_2? oscillator > Filter_Ind_2_UL ? 1 : 0 : 0 Entry_Ind_2_Short = Filter_Ind_2? oscillator < Filter_Ind_2_LL ? 1 : 0 : 0 Exit_Ind_2_Long = Entry_Ind_2_Short Exit_Ind_2_Short = Entry_Ind_2_Long //#region ~~~~~~~ASSEMBLY OF FILTERS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~} // You may have as many indicators as you like. Assemble them in similar fashion as below. // ——————— Assembly of Entry Filters Nbr_Entries = input.int(1, minval=1, title='Min Nbr Entries', inline='nbr_in_out', group='Assembly of Indicators') // Update the assembly based on the number of indicators connected. EntryLongOK = Entry_Ind_1_Long + Entry_Ind_2_Long >= Nbr_Entries? true: false EntryShortOK = Entry_Ind_1_Short + Entry_Ind_2_Short >= Nbr_Entries? true: false entry_signal = EntryLongOK ? 1 : EntryShortOK ? -1 : 0 plot(entry_signal, title="Entry_Signal", color=color.new(color.blue, 0)) // ——————— Assembly of Exit Filters Nbr_Exits = input.int(1, minval=1, title='Min Nbr of Exits', inline='nbr_in_out', group='Assembly of Indicators', tooltip='Enter the minimum number of entries & exits required for a signal.') // Update the assembly based on the number of indicators connected. ExitLongOK = Exit_Ind_1_Long + Exit_Ind_2_Long >= Nbr_Exits? true: false ExitShortOK = Exit_Ind_1_Short + Exit_Ind_2_Short >= Nbr_Exits? true: false exit_signal = ExitLongOK ? 1 : ExitShortOK ? -1 : 0 plot(exit_signal, title="Exit_Signal", color=color.new(color.red, 0)) //#endregion ~~~~~~~END OF ASSEMBLY OF FILTERS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~} The input box for the connection-indicator is shown below. The default for input source is “close”. For Input_Ind_1 click the dropdown and select the MACD Histogram. For Input_Ind_2 click the dropdown and select Aroon Up and Aroon Down as shown. Signal Connection Section of PSE Below is a description of how to connect your chosen indicators to the PSE from the connection-indicator. At the PSE Input tab, the Signal Connection Section is where you select the source of the Entry and Exit Signal to the PSE. These are the outputs from connection-indicator. The default source is “close”. Click the dropdown and select the entry and exit signal to establish a connection as shown below.
Стратегия Pine Script®
от CoinOperator
AutoPilot | FractalystWhat’s the purpose of this indicator? The AutoPilot indicator automates the management of your active trades by: Breaks Even: Moves the stop-loss to the entry price once the trade reaches a 1:1 risk-reward ratio. Closes Trades: Automatically exits trades when trailing stop-losses are triggered. This automation is facilitated through PineConnector and TradingView webhook integration, allowing traders to manage multiple positions across various markets effortlessly without any manual intervention. ---- How does this indicator trail stop-loss using market structure? The AutoPilot indicator utilizes an advanced market structure trailing stop-loss mechanism to manage trades based on market dynamics and probabilities. Here's how it works: Market Structure Identification: The indicator first identifies key market structures such as higher highs, lower lows. These structures are pivotal points where the market has shown a change in direction or momentum. Probability-Based Trailing: Once a trade is active, the stop-loss isn't just set at a fixed distance or percentage but is dynamically adjusted based on the probability of the market structure holding or breaking. This involves: Trend Continuation Probability: If the market structure suggests a strong trend continuation (e.g., a series of higher highs in an uptrend), the stop-loss might trail closer to the price, but with a buffer calculated by the probability of the trend continuing versus reversing. Reversal Probability: Conversely, if there's a high probability of a trend reversal based on recent market structures (like a significant lower high in an uptrend), the stop-loss might be adjusted to a point where the market structure would need to break to confirm the reversal, thus protecting potential profits or minimizing losses. Dynamic Adjustment: The trailing stop-loss adjusts in real-time as new market structures form. For instance, if a new higher high is formed in an uptrend, the stop-loss might move up but not necessarily to the exact previous swing low. Instead, it's placed at a level where the probability of the next swing low not breaking this level is high, based on historical price action. Risk Management: By using market structure and probabilities, the indicator aims to balance between giving the trade room to breathe (allowing for normal market fluctuations) and tightening the stop-loss when the market behavior suggests a potential trend change or continuation with high confidence. This approach ensures that the stop-loss isn't just a static or simple trailing mechanism but a sophisticated tool that adapts to the evolving market conditions, aiming to maximize profit while minimizing the risk of being stopped out prematurely due to market noise. ---- How are the probabilities calculated? What are the underlying calculations? The probability is designed to enhance trade management by using buyside liquidity and probability analysis to filter out low/high probability conditions. This helps in identifying optimal trailing points where the likelihood of a price continuation is higher. Calculations: 1. Understanding Swing highs and Swing Lows Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right. Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right. 2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels. 3. Understanding probability calculations 1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive 2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active 3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences. 5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities. Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity. ---- What does the automation table display? The automation table in the AutoPilot indicator provides a summary of user-defined settings crucial for automated trade management through PineConnector and TradingView integration. It displays: PineConnector License ID: This ensures that the indicator is linked to your specific PineConnector account, allowing for personalized and secure automation of your trades. Order Type (Buy/Sell): Indicates whether the automation is set for buying or selling, which is essential for correctly executing your trading strategy. Chosen Symbol: Specifies the trading pair or symbol in your broker's platform where the trade management commands (like closing orders) will be executed. This ensures that the automation targets the correct market or asset. Risk Per Trade: Shows the percentage or amount of your capital you're willing to risk on each trade, helping you maintain consistent risk management across different trades. Comment: A field for you to input notes or identifiers, particularly useful when trading across multiple markets or instruments. This helps in tracking and managing trades across different assets or strategies. Comment: A field for you to input identifiers, particularly useful when trading across multiple timeframes or different enries. Allowing users to manage specific comments for each previously taken entry, facilitating precise management of multiple trades with unique identifiers. This table serves as a quick reference for your current settings, ensuring you're always aware of how your trades are being managed automatically before any adjustments are made or alerts are triggered. ---- How to use the indicator? To use the AutoPilot indicator: Purchase a License ID: Acquire a license ID from PineConnector. Setup PineConnector EA: Install and configure the PineConnector Expert Advisor on your MetaTrader platform. Input Settings: Enter your PineConnector license ID, choose the order type, set your risk per trade, add the order comment, and select the trading symbol in the indicator's settings. Create Alert: Right-click on the automation table, and set up an alert with the provided webhook to connect with PineConnector. Automatic Management: Once set, your active trades will be automatically managed according to the alert conditions you've set. This setup ensures your trades are managed seamlessly without constant manual intervention. ---- What makes this indicator original? Integration with PineConnector: The AutoPilot indicator's originality lies in its integration with PineConnector, which allows for real-time trade management directly from TradingView to your MetaTrader platform. This setup is unique as it combines the analytical capabilities of TradingView with the execution capabilities of MetaTrader through a custom indicator, providing a seamless bridge between analysis and action. Market Structure-Based Trailing Stop-Loss: Unlike many indicators that might use fixed percentages or ATR (Average True Range) for stop-loss adjustments, the AutoPilot indicator uses market structure (higher highs, lower lows) to dynamically adjust the stop-loss. Probability-Based Adjustments: The indicator doesn't just trail stop-losses based on price but incorporates the probability of market structure holding or breaking. This probability-based trailing mechanism is innovative, aiming to balance between giving trades room to breathe and tightening when market behavior suggests a potential reversal or continuation. Customizable Automation Table: The automation table within the indicator allows for detailed customization, including setting specific comments for trades. This feature, while perhaps not unique in concept, is original in its implementation within trading indicators, providing users with a high degree of control and personalization over trade management. Real-Time Trade Management Alerts: The ability to set up alerts directly from the indicator to manage trades in real-time via webhooks to PineConnector adds a layer of automation that's not commonly found in standard trading indicators. This real-time connection for trade management enhances its originality by reducing the lag between analysis and trade execution. User-Centric Design: The design of the AutoPilot indicator focuses heavily on user interaction, allowing for inputs like risk per trade, specific order types, and comments. This user-centric approach, where the indicator adapts to the trader's strategy rather than the trader adapting to the tool, sets it apart. External Integration for Enhanced Functionality: By leveraging external services like PineConnector for execution, the indicator extends its functionality beyond what's typically possible within TradingView alone, making it original in its ecosystem integration for trading purposes. Practical Implication: This means if you're in a trade and the market structure suggests the trend is continuing (e.g., making higher highs in an uptrend), your stop-loss might trail closer to the price but not too close to avoid being stopped out by normal fluctuations. If the structure breaks (e.g., a lower high in an uptrend), the stop-loss could adjust more aggressively to protect profits or minimize losses, anticipating a potential trend change. This combination of features creates an original tool that not only analyzes market conditions but actively manages trades based on sophisticated market structure analysis. ---- User-input settings and customizations ---- Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. By utilizing our charting tools, the buyer acknowledges that neither the seller nor the creator assumes responsibility for decisions made using the information provided. The buyer assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses. Therefore, by purchasing these charting tools, the customer acknowledges that neither the seller nor the creator is liable for any unfavorable outcomes resulting from the development, sale, or use of the products. The buyer is responsible for canceling their subscription if they no longer wish to continue at the full retail price. Our policy does not include reimbursement, refunds, or chargebacks once the Terms and Conditions are accepted before purchase. By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer.
Индикатор Pine Script®
от Fractalyst
AlgoBuilder [Trend-Following] | FractalystWhat's the strategy's purpose and functionality? This strategy is designed for both traders and investors looking to rely on and trade based on historical and backtested data using automation. The main goal is to build profitable trend-following strategies that outperform the underlying asset in terms of returns while minimizing drawdown. For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown. Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors. In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based trailing stop-loss mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels. Additionally, the strategy has also a feature that includes a built-in probability and sentiment function for traders who want to implement probabilities and market sentiment right into their trading strategies. Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, compound annual growth rate (CAGR), profit factor, average trade, average risk-reward ratio (RR), and more. This aids optimization to meet specific goals and risk tolerance levels effectively. ----- How does the strategy perform for both investors and traders? The strategy has two main modes, tailored for different market participants: Traders and Investors. Trading: 1. Trading (1x): - Designed for traders looking to capitalize on bullish trending markets. - Utilizes a percentage risk per trade to manage risk and optimize returns. - Suitable for active trading with a focus on trend-following and risk management. - (1x) This mode ensures no stacking of positions, allowing for only one running position or trade at a time. ◓: Mode | %: Risk percentage per trade 2. Trading (2x): Similar to the 1x mode but allows for two pyramiding entries. This approach enables traders to increase their position size as the trade moves in their favor, potentially enhancing profits during strong bullish trends. ◓: Mode | %: Risk percentage per trade 3. Investing: - Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown. - Utilizes 100% of the equity to buy, hold, and manage the asset. - Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions. - ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 100% of equity to buy the asset) ----- What's the purpose of using moving averages in this strategy? What are the underlying calculations? Using moving averages is a widely-used technique to trade with the trend. The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages. The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns. By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades. The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition. This comparison filter can be turned on (>/<) or off. For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions. MA #1: Fast MA | MA #2: Medium MA | MA #3: Slow MA ⍺: MA Period | Σ: MA Timeframe ----- What entry modes are used in this strategy? What are the underlying calculations? The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal. 1. Breakout Entries : - The strategy looks for pivot high points with a default period of 3. - It stores the most recent high level in a variable. - When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot high left bars period | ◨: Pivot high right bars period 2. Fractal Entries : - The strategy looks for pivot low points with a default period of 3. - When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry. ◧: Pivot low left bars period | ◨: Pivot low right bars period By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points. ----- What type of stop-loss identification method are used in this strategy? What are the underlying calculations? Initial Stop-Loss: 1. ATR Based: The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves. Calculation: - To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close. The True Range is the largest of the following: - Current Period High minus Current Period Low - Absolute Value of Current Period High minus Previous Period Close - Absolute Value of Current Period Low minus Previous Period Close - The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14). Example - ATR (14) * 1.5 ⍺: ATR period | Σ: ATR Multiplier 2. ADR Based: The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. Calculation: - To calculate the ADR for a particular day: - Calculate the average of the high prices over a specified number of days. - Calculate the average of the low prices over the same number of days. - Find the difference between these average values. - The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements. Example - ADR (14) * 1.5 ⍺: ADR period | Σ: ADR Multiplier Application in Strategy: - The strategy calculates the current bar's ADR/ATR with a user-defined period. - It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level. By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. Trailing Stop-Loss: One of the key elements of this strategy is its ability to detec buyside and sellside liquidity levels across multiple timeframes to trail the stop-loss once the trade is in running profits. By utilizing this approach, the strategy allows enough room for price to run. There are two built-in trailing stop-loss (SL) options you can choose from while in a trade: 1. External Trailing Stop-Loss: - Uses sell-side liquidity to trail your stop-loss, allowing price to consolidate before continuation. This method is less aggressive and provides more room for price fluctuations. Example - External - Wick below the trailing SL - 12H trailing timeframe ⍺: Exit type | Σ: Trailing stop-loss timeframe 2. Internal Trailing Stop-Loss: - Uses the most recent swing low with a period of 2 to trail your stop-loss. This method is more aggressive compared to the external trailing stop-loss, as it tightens the stop-loss closer to the current price action. Example - Internal - Close below the trailing SL - 6H trailing timeframe ⍺: Exit type | Σ: Trailing stop-loss timeframe Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. ----- What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations? For Break-Even: - You can choose to set a break-even level at which your initial stop-loss moves to the entry price as soon as it hits, and your trailing stop-loss gets activated (if enabled). - You can select either a percentage (%) or risk-to-reward (RR) based break-even, allowing you to set your break-even level as a percentage amount above the entry price or based on RR. For TP1 (Take Profit 1): - You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled. - Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR. For TP2 (Take Profit 2): - You can choose to set a take profit level at which your position gets fully closed. - As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR. The underlying calculations involve determining the price levels at which these actions are triggered. For break-even, it moves the initial stop-loss to the entry price and activate the trailing stop-loss once the break-even level is reached. For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price. These calculations are crucial for managing risk and optimizing profitability in the strategy. ⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price ----- What's the ADR filter? What does it do? What are the underlying calculations? The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days. The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss. Users can define the minimum ADR they want to be met before the script looks for entry conditions. ADR Bias Filter: - Compares the current bar ADR with the ADR (Defined by user): - If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆) - If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇) Calculations: 1. Calculate ADR: - Average the high prices over the specified period. - Average the low prices over the same period. - Find the difference between these average values in %. 2. Current ADR vs. ADR (DbU): - Calculate the ADR for the current bar. - Calculate the ADR (DbU). - Compare the two values to determine if volatility has increased or decreased. By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy. >: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago. ----- What's the probability filter? What are the underlying calculations? The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions. This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher. Calculations: 1. Understanding Swing highs and Swing Lows Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right. Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right. 2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels. 3. Understanding probability calculations 1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive 2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active 3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences. 5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities. Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity. Example - BSL > 50% ----- What's the sentiment Filter? What are the underlying calculations? Sentiment filter aims to calculate the percentage level of bullish or bearish fluctuations within equally divided price sections, in the latest price range. Calculations: This filter calculates the current sentiment by identifying the highest swing high and the lowest swing low, then evenly dividing the distance between them into percentage amounts. If the price is above the 50% mark, it indicates bullishness, whereas if it's below 50%, it suggests bearishness. Sentiment Bias Identification: Bullish Bias: The current price is trading above the 50% daily range. Bearish Bias: The current price is trading below the 50% daily range. Example - Sentiment Enabled | Bullish degree above 50% | Bullish sentimental bias >: Minimum required sentiment for entry | %: Current sentimental degree in a (Bullish/Bearish) sentimental bias ----- What's the range length Filter? What are the underlying calculations? The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement. Calculations: Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100 Range Bias Identification: Bullish Bias: The current range price has broken above the previous external swing high. Bearish Bias: The current range price has broken below the previous external swing low. Example - Range length filter is enabled | Range must be above 5% | Price must be in a bearish range >: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range ----- What's the day filter Filter, what does it do? The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style. Customize Session Time: Users can define the start and end times for the trading session. This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours. Select Days: Users can select which days of the week to include in the strategy. This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays). Benefits: Focus on Optimal Trading Periods: By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities. Avoid Unfavorable Conditions: Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays. Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences. Example - Day filter | Session Filter θ: Session time | Exchange time-zone ----- What tables are available in this script? Table Type: - Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades, Compound Annual Growth Rate (CAGR), MAR and more. CAGR: It calculates the 'Compound Annual Growth Rate' first and last taken trades on your chart. The ​CAGR is a notional, annualized growth rate that assumes all profits are reinvested. It only takes into account the prices of the two end points — not drawdowns, so it does not calculate risk. It can be used as a yardstick to compare the performance of two strategies. Since it annualizes values, it requires a minimum 4H timeframe to display the CAGR value. annualizing returns over smaller periods of times doesn't produce very meaningful figures. MAR: Measure of return adjusted for risk: CAGR divided by Max Drawdown. Indicates how comfortable the system might be to trade. Higher than 0.5 is ideal, 1.0 and above is very good, and anything above 3.0 should be considered suspicious and you need to make sure the total number of trades are high enough by running a Deep Backtest in strategy tester. (available for TradingView Premium users.) Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit. MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position. Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses. Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit. Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most trend-following successful strategies have a percent profitability of 15-40% but are profitable due to risk management control. BE Trades: Number of break-even trades, excluding commission/slippage. Losing Trades: The total number of losing trades generated by the strategy. Winning Trades: The total number of winning trades generated by the strategy. Total Trades: Total number of taken traders visible your charts. Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign. - Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month. - Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations. - OFF: Hides the performance table. Labels: - OFF: Hides labels in the performance table. - PnL: Shows the profit and loss of each trade individually, providing detailed insights into the performance of each trade. - Range: Shows the range length and Average Day Range (ADR), offering additional context about market conditions during each trade. Profit Color: - Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods. Loss Color: - Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods. These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization. ----- User-input styles and customizations: To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions. Please note that all background colors in the style are disabled by default to enhance visualization. ----- How to Use This Algobuilder to Create a Profitable Edge and System: Choose Your Strategy mode: - Decide whether you are creating an investing strategy or a trading strategy. Select a Market: - Choose a one-sided market such as stocks, indices, or cryptocurrencies. Historical Data: - Ensure the historical data covers at least 10 years of price action for robust backtesting. Timeframe Selection: - Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions on your profits. Set Commission and Slippage: - Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications. Parameter Optimization: - Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester. Trade Count: - Ensure the number of trades is 100 or more; the higher, the better for statistical significance. Positive Average Trade: - Make sure the average trade value is above zero. (An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.) Performance Metrics: - Look for a high profit factor, MAR (Mar Ratio), CAGR (Compound Annual Growth Rate), and net profit with minimum drawdown. Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance. Refinement and Optimization: - Try out different markets and timeframes. - Continue working on refining your edge using the available filters and components to further optimize your strategy. Automation: - Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm. - Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management. ----- What makes this strategy original? 1. Incorporating direct integration of probabilities into the strategy. 2. Leveraging market sentiment to construct a profitable approach. 3. Utilizing built-in market structure-based trailing stop-loss mechanisms across various timeframes. 4. Offering both investing and trading strategies, facilitating optimization from different perspectives. 5. Automation for efficient execution. 6. Providing a summary table for instant access to key parameters of the strategy. ----- How to use automation? For Traders: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Enter your PineConnector License ID in the designated field. 3. Specify the desired risk level. 4. Provide the Metatrader symbol. 5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol. 6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}. 7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address. 8. Double-check all settings on PineConnector to ensure the connection is successful. 9. Create the alert for entry/exit automation. For Investors: 1. Ensure the strategy parameters are properly set based on your optimized parameters. 2. Choose "Investing" in the user-input settings. 3. Create an alert with a specified name. 4. Customize the notifications tab to receive alerts via email. 5. Buying/selling alerts will be triggered instantly upon entry or exit order execution. ---- Strategy Properties This script backtest is done on 4H COINBASE:BTCUSD , using the following backtesting properties: Balance: $5000 Order Size: 10% of the equity Risk % per trade: 1% Commission: 0.04% (Default commission percentage according to TradingView competitions rules) Slippage: 75 ticks Pyramiding: 2 ----- Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited. By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Стратегия Pine Script®
от Fractalyst
3
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy 1. Introduction Purpose of the Handbook: The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios. Overview of the Supertrend Advance Pullback Strategy: At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals. 1. Basic Concept: The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends. 2. Methodology: Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise. 3. Benefits: One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points. 4. Practical Applications: The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies. In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading. As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors. 2. Getting Started Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time. Setting up on TradingView: TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how: 1. Account Creation: • Visit TradingView's official website. • Click on the "Join for free" or "Sign up" button. • Follow the registration process, providing the necessary details and setting up your login credentials. 2. Navigating the Dashboard: • Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window. • To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top. 3. Configuring Chart Settings: • Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window. • Adjust the chart type, time intervals, and other display settings to your preference. Integrating the Strategy into a Chart: Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy. 1. Accessing the Pine Script Editor: • Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it. • This is where custom strategies and indicators are scripted or imported. 2. Loading the Supertrend Advance Strategy Script: • Depending on whether you have the script or need to find it, there are two paths: • If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor. • If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart. 3. Applying the Strategy: • After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window. 4. Configuring Strategy Settings: • Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings. • Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing. 5. Interpreting Signals: • With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions. 3. Strategy Overview What is the Supertrend Advance Strategy? The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals. In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point. Strategy Goals and Objectives: 1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor. 2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making. 3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability. 4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system. Type of Assets/Markets to Apply the Strategy: 1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices. 2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders. 3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements. 4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters. 5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits. It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades. 4. Input Settings Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance. Grouping Inputs: Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator. Strategy Choice: This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available. Supertrend Settings: 1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer. 2. Period: The number of bars used in the ATR calculation. A common default is 7. EMA Settings (Exponential Moving Average): 1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200. 2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation. RSI Settings (Relative Strength Index): 1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14. 2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70. 3. Oversold Level: The threshold at which the asset is considered oversold, often at 30. MACD Settings (Moving Average Convergence Divergence): 1. Short Period: The shorter EMA, usually set to 12. 2. Long Period: The longer EMA, commonly set to 26. 3. Signal Period: Defines the EMA of the MACD line, typically set at 9. CCI Settings (Commodity Channel Index): 1. Period: The number of bars used in the CCI calculation, often set to 20. 2. Overbought Level: Typically set at +100, denoting overbought conditions. 3. Oversold Level: Usually set at -100, indicating oversold conditions. SL/TP Settings (Stop Loss/Take Profit): 1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss. 2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit. Filtering Conditions: This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions. Trade Direction and Backtest Period: 1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both. 2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc. It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy. 5. Understanding Strategy Conditions Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point. Basic Logic Behind Conditions: Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future. Buy and Sell Conditions: 1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum. 2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum. Simple Strategy: The simple strategy could involve using just the Supertrend indicator. Here: • Buy: When price closes above the Supertrend line. • Sell: When price closes below the Supertrend line. Pullback Strategy: This strategy capitalizes on price retracements: • Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator. • Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator. Indicators Used: EMA (Exponential Moving Average): • Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish. RSI (Relative Strength Index): • Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold. MACD (Moving Average Convergence Divergence): • Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish. CCI (Commodity Channel Index): • Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition. And others... As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives. Logic Behind Each Indicator: 1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels. 2. RSI: Indicates overbought and oversold conditions based on recent price changes. 3. MACD: Showcases momentum and direction of a trend by comparing two EMAs. 4. CCI: Measures the difference between a security's price change and its average price change. Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets. 6. Trade Execution and Management Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy. Position Entry: Effective trade entry revolves around: 1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators. 2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal. 3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover. Position Exit Strategies: A successful exit strategy will lock in profits and minimize losses. Here are some strategies: 1. Fixed Time Exit: Exiting after a predetermined period. 2. Percentage-based Profit Target: Exiting after a certain percentage gain. 3. Indicator-based Exit: Exiting when an indicator gives an opposing signal. Percentage-based SL/TP: • Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses. • Example: A 2% SL on an entry at $100 would trigger a sell at $98. • Take Profit (TP): Set a fixed percentage above the entry price to lock in gains. • Example: A 5% TP on an entry at $100 would trigger a sell at $105. Supertrend-based SL/TP: • Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal. • Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum. Swing high/low-based SL/TP: • Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high. • Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support. And other methods... 1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor. 2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages. 3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal. Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance. 7. Visual Representations Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance. Understanding Plots on the Chart: Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves. 1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day. 2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves. Trend Lines: Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance: 1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal. 2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend. Filled Areas: These represent a range between two values on a chart, usually shaded or colored. For instance: 1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility. 2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels. Stop Loss and Take Profit Lines: These are horizontal lines representing pre-determined exit points for trades. 1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance. 2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors. Trailing Stop Lines: A trailing stop is a dynamic form of stop loss that moves with the price. On a chart: 1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in. 2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises. Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results. 8. Backtesting Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of. Setting Up Backtest Period: 1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years. 2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results. 3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments. Analyzing Backtest Results: 1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency. 2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics. 3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss. 4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover. 9. Tips and Best Practices Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy. When to Use the Strategy: 1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets. 2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news. 3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume. Adjusting Settings for Different Markets/Timeframes: 1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity. 2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes. 3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions. 10. Frequently Asked Questions (FAQs) Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy. 1. What exactly is the Supertrend Advance Strategy? The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals. 2. Can I use the Supertrend Advance Strategy for all asset types? Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type. 3. Is this strategy suitable for day trading? Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on. 4. How do I deal with false signals? No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals. 5. Do I need any prior trading experience to use this strategy? While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts. 6. How often should I review and adjust the strategy settings? There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments. 7. Can the Supertrend Advance Strategy be automated? Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended. 8. Are there any markets or conditions where the strategy shouldn't be used? The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market. 9. How important is backtesting with this strategy? Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades. 10. What if the strategy isn't working for me? No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success. Other comments Value of combining several indicators in this script and how they work together Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point. Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced. Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios. Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market. How do the different indicators in the Supertrend Advance Strategy work together? Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends. EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa. RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend. MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend. CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points. In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions. Backtesting and Default Settings • This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts. • This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security. • The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year. • Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security. • Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
Стратегия Pine Script®
от JS_TechTrading
1
Trend Targets Oscillator- Webhooks v1.8.3Trend Targets Oscillator - Webhooks v1.8.3 Overview This technical indicator combines a momentum-based oscillator with statistical analysis of historical price behavior to generate trading signals and calculate position management levels. The indicator analyzes past price patterns to establish data-driven thresholds for entries, exits, and stop placement. Key Components: • Weighted momentum oscillator with trend-following characteristics • Statistical percentile analysis for take profit level calculation • Dynamic stop loss placement based on price structure and volatility • Adaptive ranges (ATR-based) for dynamic support/resistance visualization • Real-time performance tracking and historical signal analysis Critical Disclaimer: This indicator performs technical analysis on historical data. Past patterns, statistics, and performance do not predict, indicate, or guarantee future results. All trading carries substantial risk of loss. This tool does not provide investment advice or trading recommendations. Important Note: Calculations use standard OHLC data; results may differ on non-standard chart types (Heikin Ashi, Renko, Kagi, Point & Figure, Range). Technical Methodology 1. Momentum Oscillator Core Approach: The oscillator employs a weighted Relative Strength Index (RSI) methodology combined with Quantitative Qualitative Estimation (QQE) trailing stop concepts. This creates a momentum indicator that adapts to trending conditions while maintaining sensitivity to reversals. How It Functions: • Calculates directional price momentum using weighted price changes • Applies directional bias to amplify movements aligned with the prevailing trend direction • Uses a dynamic trailing stop mechanism adapted from QQE methodology to identify potential trend reversals • Applies exponential moving average smoothing to reduce market noise • Operates within configurable overbought/oversold threshold zones (default: 70/30) Signal Generation Process: • BUY signals occur when the oscillator line crosses above its trailing stop level • SELL signals occur when the oscillator line crosses below its trailing stop level • All signals confirm only at bar close, eliminating mid-bar fluctuations and repainting Technical Parameters (All Configurable): • RSI Length (default: 100 bars) - Controls the period for momentum calculation • Stop Multiplier (default: 2.5) - Adjusts the sensitivity of the trailing stop mechanism • Smoothing Length (default: 6 bars) - Reduces noise through exponential smoothing • Directional Weight (default: 6.4) - Amplifies trend-aligned price movements • Overbought/Oversold Levels (default: 70/30) - Defines momentum extreme zones What This Component Does: This component identifies potential trend changes through momentum analysis, generates entry signals based on the interaction between an oscillator and a trailing stop, filters those signals using overbought and oversold zones, and confirms all signals at bar close to help prevent repainting. What This Component Does Not Do: This component does not predict future price direction or guarantee signal accuracy or profitability, it cannot eliminate false signals entirely, and it will not perform equally well across all market conditions. 2. Statistical Take Profit Calculation Methodology: Rather than using fixed risk-reward ratios, this indicator analyzes the Maximum Favorable Excursion (MFE) from historical signals to establish statistically-derived take profit levels using percentile (quantile) analysis. Maximum Favorable Excursion (MFE) Concept: MFE measures how far price moved in the favorable direction after each historical signal before either reversing or hitting the stop loss. This creates a dataset of historical "best case" price movements for each direction. Statistical Process: • Maintains separate historical datasets for LONG signals and SHORT signals (markets behave differently in uptrends vs downtrends) • Tracks MFE data from the last N signals (configurable, default: 20 signals per direction) • Calculates percentiles (quantiles) from this historical MFE dataset • Uses these percentiles to determine take profit distance from entry Three Statistical Thresholds: TP1: • Default: 66th percentile of historical MFE data • Meaning: Based on historical analysis, approximately 66% of similar past signals moved at least this far in the favorable direction • Note: This is a statistical observation of past behavior, not a prediction that 66% of future signals will reach this level TP2: • Default: 50th percentile (median) of historical MFE data • Meaning: Represents the middle point of historical favorable price movements • Note: Past median values do not indicate future median performance TP3: • Default: 30th percentile of historical MFE data • Meaning: Based on historical analysis, approximately 30% of similar past signals moved at least this far Important Technical Notes: • Percentile thresholds are fully configurable in settings (you can adjust 66/50/30 to any values) • Requires minimum historical data (20+ signals per direction) for statistical relevance • Falls back to configurable risk-reward ratio (default 1.5R) when insufficient historical data exists • Recalculates dynamically as new signals complete and add to the historical dataset • "R" represents Risk units (distance from entry to stop loss) What This Component Does: This component analyzes historical price behavior patterns and calculates statistical percentiles from past favorable movements to establish take-profit levels based on observed historical data. It adapts to the specific instrument and timeframe being analyzed, and it separates its analysis for long versus short signals. What This Component Does Not Do: This component does not predict where future price will reach or guarantee any specific hit rate or success percentage, and it cannot ensure profits on any individual trade. It also does not account for changing market conditions or regime shifts, and it does not replace the need for proper risk management and position sizing. 3. Dynamic Stop Loss Placement Methodology: Stop loss calculation combines Donchian Channel logic with Average True Range (ATR) volatility adjustment to create stops that respect recent price structure while accounting for normal market fluctuations. How It Functions: Donchian Channel Component: • Identifies the highest high and lowest low over a specified lookback period (default: 20 bars) • For LONG signals: Uses the lowest low as the base for stop placement • For SHORT signals: Uses the highest high as the base for stop placement • This respects recent price structure and support/resistance levels ATR Volatility Buffer: • Calculates the Average True Range over 14 periods to measure current volatility • Adds a configurable buffer (default: 1.0 × ATR) beyond the Donchian extreme • For LONG signals: Stop = Donchian Low - (ATR × Buffer Multiplier) • For SHORT signals: Stop = Donchian High + (ATR × Buffer Multiplier) • This prevents premature stop-outs from normal price volatility Technical Parameters (All Configurable): • Donchian Length (default: 20 bars) - Period for identifying recent price extremes • SL Buffer Multiplier (default: 1.0 × ATR) - Distance beyond Donchian extreme (0.0 to 5.0) What This Component Does: This component places stops based on recent price structure using Donchian extremes, adjusts them to reflect current volatility via an ATR-based offset, and adapts dynamically as conditions change. It includes a configurable buffer to suit different trading styles and is designed to respect key technical support and resistance levels. What This Component Does Not Do: This component does not guarantee that a stop loss will not be hit, nor can it prevent slippage, gaps, or other execution-related risks. It does not ensure a favorable risk-reward outcome on every trade, does not account for fundamental events or news releases, and it does not replace the need for proper position sizing and overall capital management. 4. Adaptive Ranges (ATR-Based) Methodology: The indicator includes an optional overlay that displays adaptive support and resistance zones based on Average True Range (ATR) volatility measurements. These ranges adjust dynamically as price moves beyond volatility thresholds. How It Functions: • Calculates an adaptive moving average that shifts when price moves beyond ATR-based thresholds • Displays five levels: Upper Resistance 2 (R2), Upper Resistance 1 (R1), Middle (AVG), Lower Support 1 (S1), Lower Support 2 (S2) • Zones are created using ATR multiples above and below the adaptive average • When price breaches the outer boundaries significantly, the entire range structure recalculates and repositions Technical Parameters (All Configurable): • Length (default: 50 bars) - Period for ATR calculation • Factor (default: 6.0) - Multiplier for ATR to set zone width • Source (default: close) - Price data used for calculations • Show (default: ON) - Toggle visibility Purpose and Use: • Provides context for potential reversal or consolidation areas • Can complement the statistical TP levels by showing additional resistance/support • Helps visualize market volatility expansion and contraction • Creates dynamic zones that adapt to changing volatility conditions What This Component Does: This component displays volatility-adjusted support and resistance zones, adapt dynamically to price movement and changing volatility, providing visual context for potential reversal areas. The segments update when price moves beyond defined threshold boundaries. What This Component Does Not Do: This component does not predict future support or resistance levels, does not guarantee that reversals will occur at zone boundaries, or replace traditional support and resistance analysis. It also does not account for fundamental catalysts or news-driven events that can override technical behavior. Visual Components and Displays Oscillator Panel (Lower Pane) The oscillator displays in a separate pane below the price chart with the following elements: • Main Oscillator Line (teal/green): Shows current momentum state • Trailing Stop Line (purple): Dynamic support/resistance level that triggers signals • Overbought/Oversold Zones: Horizontal threshold lines (default 70/30) • Historical Signal Markers: BUY (green triangles up) and SELL (red triangles down) where signals occurred Reading the Display: - When oscillator crosses above trailing stop = BUY signal generated - When oscillator crosses below trailing stop = SELL signal generated - Oscillator in upper zone (>70) = momentum in overbought territory - Oscillator in lower zone (<30) = momentum in oversold territory On-Chart Overlays (Price Chart) For each historical signal, the indicator displays visual overlays on the main price chart: Entry Line (Yellow): - Horizontal line showing the price level where the signal was generated - Helps identify the actual entry point Stop Loss Line (Red): - Horizontal line showing the calculated stop loss level - Based on Donchian + ATR methodology described above Three Take Profit Zones (Green for LONG / Red for SHORT): - TP1 Zone: Lightest shade - conservative percentile target - TP2 Zone: Medium shade - moderate percentile target - TP3 Zone: Darkest shade - aggressive percentile target - Zones displayed as shaded rectangular areas extending forward from signal Visual historical overlays: This provides visual feedback on historical signal performance and helps assess whether the statistical methodology is appropriate for the current instrument and timeframe. These visual overlays allow you to see: These visual overlays allow you to see where historical signals occurred and at what price, where stops were placed according to the methodology, and where statistical take-profit levels were calculated. They also show which targets were reached versus not reached, how price behaved relative to the statistical projections, and the adaptive support/resistance context that frames overall market structure. Statistics Table (Real-Time Analysis) The indicator displays a comprehensive statistics table (typically in the upper-right corner) showing performance metrics for historical signals. Table Header: "Historical stats (not predictive) under current settings" Performance Metrics (Separate rows for BUY and SELL): For the Last N Signals (default: last 20 BUY and last 20 SELL separately): Column Headers: • Signal: Direction (BUY or SELL) • Win: Count of signals where at least one take profit was reached before stop loss • Loss: Count of signals where stop loss was hit before any take profit was reached • TP1 Hit: Percentage of signals that reached the first take profit level • Δ1%: Average percentage distance from entry to TP1, calculated only for signals that actually reached TP1 • TP2 Hit: Percentage of signals that reached the second take profit level • Δ2%: Average percentage distance from entry to TP2, calculated only for signals that actually reached TP2 • TP3 Hit: Percentage of signals that reached the third take profit level • Δ3%: Average percentage distance from entry to TP3, calculated only for signals that actually reached TP3 Understanding the Distance Metrics: The "Dist%" columns show the average percentage gain (from entry price to TP level) for only those trades that successfully reached that specific TP level. This helps you understand the typical profit magnitude when that target is hit. Footer Message (Historical Performance Evaluation): The table displays one of three messages based on historical loss percentage: ✅ "Historical performance threshold met. Based on past data under current settings. Not a recommendation." - Displayed when both LONG and SHORT directions show less than 40% losses on past historical data on this specific instrument and timeframe - indicates the loss-rate is below the configured threshold (40% losses) for both directions over the last N historical observations (descriptive only). 🛑 "Historical performance below threshold. Based on past data under current settings. Not a recommendation." - Displayed when both LONG and SHORT directions show more than 40% losses on past historical data on this specific instrument and timeframe - indicates the loss-rate is above the configured threshold (40% losses) for both directions over the last N historical observations (descriptive only). ⚠️ "Historical performance: Mixed / higher risk. Based on past data under current settings. Not a recommendation." - Displayed when one direction is <40% loss and one is >40% loss on past historical data on this specific instrument and timeframe - indicates a mixed result: one direction is above and the other is below the threshold over the last N historical observations (descriptive only). These statistics and messages are descriptive of past historical performance for the specific instrument and timeframe being analyzed, and they are provided purely as informational tools to help you understand how the indicator behaved historically. They are based solely on historical data analysis and can change over time as new signals complete and the underlying dataset updates. These statistics and messages are not predictions of future performance, trading recommendations or advice, or guarantees of profitability. They do not indicate that past results will repeat, and they should not be interpreted as suggestions to enter trades or to avoid them. The footer message helps you understand whether the current settings and statistical thresholds have shown historically favorable or unfavorable results on this particular market. However, past favorable statistics do not ensure future favorable results, and past unfavorable statistics do not ensure future unfavorable results. Configuration Options All parameters are fully adjustable in the indicator settings. Default values are provided as starting points and may require optimization for different instruments and timeframes. Oscillator Parameters • RSI Length (default: 100) Controls the period used for momentum calculation. Higher values = smoother, slower momentum readings. Lower values = more responsive, potentially noisier readings. • Stop Multiplier / QQE Factor (default: 2.5) Controls sensitivity of the trailing stop mechanism. Higher values = wider trailing stop, fewer signals, more trend-following. Lower values = tighter trailing stop, more signals, more sensitive to reversals. • Smoothing Length (default: 6) EMA smoothing applied to reduce noise. Higher values = smoother oscillator line. Lower values = more responsive to price changes. • Directional Weight (default: 6.4) Amplification factor for trend-aligned movements. Higher values = stronger bias toward current trend direction. Lower values = more balanced, less trend-biased. • Source (default: close) Price data used for calculations (close, open, high, low, hl2, hlc3, ohlc4). Threshold Parameters • Overbought Level (default: 70) Oscillator level considered overbought. Range: 0-100. Used for signal filtering and visual reference. • Oversold Level (default: 30) Oscillator level considered oversold. Range: 0-100. Used for signal filtering and visual reference. Statistical Analysis Parameters (Historical Percentile Targets) • Lookback N Trades (default: 20) Number of historical signals to include in statistical analysis. Analyzed separately for LONG and SHORT. Higher values = more stable statistics, slower adaptation. Lower values = more adaptive, potentially less stable statistics. Minimum: 5 signals. • TP1 Target Percentile (default: 66) Percentile of historical MFE data used for first take profit. Range: 1-99. 66 means ~66% of historical signals reached at least this distance. Higher percentile = more conservative target (closer to entry). Lower percentile = more aggressive target (farther from entry). • TP2 Target Percentile (default: 50) Percentile of historical MFE data used for second take profit. 50 = median of historical favorable movements. Adjust based on desired risk-reward profile. • TP3 Target Percentile (default: 30) Percentile of historical MFE data used for third take profit. 30 means ~30% of historical signals reached at least this distance. More aggressive, historically reached less frequently. • Fallback TP (default: 1.50 R) Risk-reward ratio used when insufficient historical data exists. "R" = Risk units (distance from entry to stop loss). 1.50 R = take profit placed at 1.5× the distance to stop loss. Used until enough signals accumulate for statistical calculation. Note on Percentile Configuration: You can customize these percentiles to match your trading style: - Conservative approach: Use higher percentiles (e.g., 80/60/40) for closer, more frequently reached targets - Aggressive approach: Use lower percentiles (e.g., 50/30/15) for extended targets with lower historical hit rates - Balanced approach: Default values (66/50/30) provide middle ground Stop Loss Parameters • Donchian Length (default: 20) Lookback period for identifying recent price extremes. Higher values = stops based on longer-term structure. Lower values = stops based on shorter-term swings. • SL Buffer (× ATR) (default: 1.00) Multiplier for ATR-based volatility buffer. Range: 0.0-5.0. 1.0 = stop placed one ATR beyond Donchian extreme. Higher values = wider stops, less risk of premature stop-out. Lower values = tighter stops, higher risk of normal volatility hitting stop. Adaptive Ranges (ATR-Based) Parameters • Length (default: 50) Period for ATR calculation used in adaptive range zones. Higher values = zones based on longer-term volatility. Lower values = zones more responsive to recent volatility changes. • Factor (default: 6.0) Multiplier applied to ATR for determining zone width. Higher values = wider zones, farther from average. Lower values = tighter zones, closer to average. • Source (default: close) Price data used for adaptive average calculation. • Show (default: ON) Toggle visibility of adaptive range overlays on chart. Turn OFF for cleaner chart if you only want oscillator signals. Visual Display Parameters • Show Historical B/S Markers (Pane) (default: ON): Displays BUY/SELL triangles in oscillator panel. • Show B/S on Price Chart (default: ON): Displays BUY/SELL markers on main price chart. • Show History TP/SL Overlays (default: ON): Displays entry lines, stop lines, and TP zones on price chart. Turn OFF for cleaner chart if you only want the oscillator signals. • History Segment Length (Bars) (default: 20): How many bars forward the TP/SL overlays extend from signal. Range: 5-200 bars. Does not affect calculations, only visual display duration. Initial Setup and Learning Period 1. Adding Indicator to Chart The indicator can be applied to any instrument and timeframe. Default settings are provided as a starting point. 2. Data Collection Period The statistical analysis requires historical signals to function. Typically 20+ bars provide initial data, while 50-100+ bars may produce more robust statistics. The table displays "Not enough data yet to evaluate" until sufficient signals exist. 3. Observing Initial Performance Signals develop over time. The calculated TP levels appear relative to actual price movement. Historical statistics show which direction (LONG vs SHORT) has performed differently. The statistics table displays historical behavior patterns. 4. Statistical Data Accumulation The indicator accumulates historical data over time. Some traders choose to observe performance in paper trading or demo environments before live use. Understanding the methodology involves reviewing how calculations work on historical data. Webhook Integration and Alerts The indicator includes alert functionality for integration with automated trading systems and notification services. Alert Characteristics: • Alerts trigger only when signals confirm at bar close (no mid-bar alerts) • Respects the historical performance evaluation footer status • Includes symbol, timeframe, and direction information in alert message • Provides JSON-formatted data for easy parsing by automated systems • Separate alert events for: Entry, TP1, TP2, TP3, Stop Loss, Early Close (Win/Loss) Alert Events Available: - Entry: When a new signal is generated - TP1/TP2/TP3: When each take profit level is reached - SL: When stop loss is hit - Early Close Win: When position closes early in profit (without hitting TP or SL) - Early Close Loss: When position closes early at a loss (without hitting TP or SL) JSON Data Structure: Each alert contains structured data including: • Event type (Entry, TP1, TP2, TP3, SL, etc.) • Direction (long/short) • Symbol and timeframe • Price levels (entry, stop, take profits) • Timestamps (entry time, event time) • Duration (milliseconds and minutes from entry to event) Compatible With: • Third-party webhook automation platforms and tools that support TradingView webhooks • Custom trading bot implementations via webhook endpoints • Notification systems that can receive TradingView alerts • Any service supporting webhook integration through TradingView's alert system The author and indicator provider assume no responsibility for losses incurred through automated trading, alert-based systems, webhook implementations, or any third-party integrations. Users are solely responsible for their trading decisions, automation setup, risk management, and system monitoring. What This Indicator Is and Is Not What This Indicator Is: This indicator is a technical analysis tool that combines momentum oscillation with statistical analysis, using a signal-generation methodology built on weighted RSI and QQE concepts. It calculates take-profit levels through historical percentile analysis, places stop losses based on both price structure and volatility, and displays adaptive support/resistance zones derived from ATR. In addition, it tracks and presents historical signal performance and serves as an educational resource for understanding statistical approaches to trading. For accurate results, it requires standard OHLC chart data. What This Indicator Is Not: This indicator is not a prediction system or “fortune-telling” tool, nor is it a guaranteed profit generator or a “holy grail” trading system. It does not provide investment advice or financial recommendations, and it is not a substitute for proper education and solid risk management. It may not be suitable for every trader, market, chart type, or market condition, and it is not a replacement for human judgment and decision-making. It also cannot eliminate the possibility of losses, drawdowns, or periods of underperformance, and it is not designed for or tested on non-standard chart types—so results may differ when used outside standard charts. Who This Indicator Is Designed For May Be Suitable For: This indicator may be suitable for traders who prefer systematic, rules-based approaches and want to incorporate statistical analysis into their trading, especially if they’re looking for a methodology that adapts to historical price behavior. It’s best for users who are comfortable with technical analysis concepts, can manage risk and position sizing properly, and are willing to invest time in testing and optimization. It also fits those who understand that past results don’t guarantee future performance and who use standard OHLC charts for their analysis. May Not Be Suitable For: This indicator may not be suitable for absolute beginners with no trading experience, or for traders looking for guaranteed profits and “get rich quick” systems. It’s also not ideal for those who are uncomfortable with technical analysis or statistical concepts, who cannot tolerate losses or drawdown periods, or who are unwilling to spend time learning, testing, and refining the methodology. Additionally, it may not fit users seeking a fully automated “set and forget” solution, traders who don’t follow proper risk management principles, or those who primarily work with non-standard chart types. Important Limitations and Considerations Technical Limitations: This indicator has several technical limitations: it requires sufficient historical data for its statistical calculations to work properly, and its performance can vary significantly across different instruments and timeframes. It may perform poorly in ranging, choppy, or low-liquidity markets, and the statistical percentiles it uses are derived from past data that may not reflect future behavior. Depending on market conditions, signals can cluster or become sparse, and no technical system performs equally well across all regimes. Results may also differ on non-standard chart types (such as Heikin Ashi, Renko, Kagi, Point & Figure, or Range charts), and while the adaptive ranges adjust to volatility, they cannot predict regime changes. Market Limitations: This indicator has market-related limitations because it cannot account for fundamental events, news, or black swan scenarios, and it does not incorporate market sentiment, positioning, or order flow. Historical statistical patterns can break down during regime shifts, and as market structure evolves, past behaviors may not persist. External drivers such as geopolitical developments or policy changes are also outside its scope, and risks from gaps as well as weekend or overnight moves are not explicitly factored into its calculations. Execution Limitations: This indicator has execution limitations because it does not account for slippage, spread, or execution delays, and it cannot guarantee fills at the calculated levels. It also does not explicitly factor in gap risk or overnight holding risk, and it assumes there is sufficient liquidity to execute orders as intended. In addition, it cannot account for exchange outages or other technical failures, and webhook or alert delivery can fail due to connectivity problems or third-party system issues. User Limitations: This indicator also has user-related limitations: it requires the discipline to follow signals consistently rather than overriding them emotionally, along with proper position sizing and risk management. Users need the psychological resilience to handle losing streaks and the time to monitor performance and evaluate results on an ongoing basis, especially if using alerts or automation. It also assumes sufficient capital and emotional reserves to withstand drawdowns, as well as a clear understanding of the constraints of standard OHLC charts. Risk Warnings and Disclaimers Please Read This Section Carefully General Trading Risks: Trading and investing involve substantial risk of loss, and you can lose some or even all of your invested capital. Past performance does not indicate, predict, or guarantee future results, and no trading system, indicator, or methodology can eliminate risk. Markets are inherently unpredictable and uncertain, so outcomes can vary widely even when using a consistent approach. Specific Risks Related to This Indicator: Its historical statistics and percentile calculations are inherently backward-looking, not forward-looking, and past favorable results do not ensure future favorable results. Market conditions can change, historical patterns may stop working or fail to repeat, and statistical analysis cannot predict future price movements. As a result, the indicator can generate losing signals and experience unprofitable periods, with no guarantee of any particular win rate, profit level, or overall performance. Metrics such as “Dist%” reflect historical averages and should not be interpreted as future profit guarantees, while adaptive ranges reflect historical volatility behavior not future support or resistance. Results may also differ significantly when used on non-standard chart types. What This Indicator Does Not Guarantee: This indicator does not guarantee profitable trades or positive returns, any specific win percentage, success rate, or profit distance, or protection from losses and drawdowns. It also cannot guarantee that historical statistics will persist into the future, that it will be suitable for your specific financial situation, or that it will match your risk tolerance or trading goals. In addition, it does not guarantee reliable operation when used with automated trading systems, nor does it guarantee consistent results across different chart types. Regulatory Disclaimer: This indicator is a technical analysis tool for educational and informational purposes only. It does not constitute: Investment advice or recommendations, Financial planning or wealth management services, A solicitation to buy or sell any securities or instruments, A guarantee or warranty of any kind regarding performance, Professional advice tailored to your specific situation Legal Liability: By using this indicator, users acknowledge and agree that they are solely responsible for all trading decisions and outcomes, and that the author and indicator provider assume no liability for any losses or damages. Users confirm that they have read and understood all stated risks and disclaimers, agree not to hold the author or provider responsible for any results, and recognize that trading can result in the total loss of capital. They also understand the limitations related to chart types and the indicator’s calculation methods, which may affect how results are produced and interpreted. Geographic Restrictions: This indicator may not be suitable or legal in all jurisdictions. It is your responsibility to ensure compliance with local laws and regulations regarding trading and financial markets. Final Statement This indicator represents a systematic approach to technical analysis that combines momentum oscillation with statistical analysis of historical price behavior and adaptive volatility-based ranges. It is designed to provide a structured framework for visualizing historical market conditions and statistical behavior under the selected settings. Access and Support Information This is an invite-only indicator. For access requests, detailed documentation, setup guides, and ongoing support, please refer to the author's signature field displayed below this publication. Thank you for taking the time to read this complete description. Understanding the methodology, limitations, and proper usage is essential for anyone considering using this indicator. Trade safely and responsibly.
Индикатор Pine Script®
от CryptogenixClub
GKD-BT Full Giga Kaleidoscope Backtest [Loxx]Giga Kaleidoscope GKD-BT Full Giga Kaleidoscope Backtest is a Backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System". █ GKD-BT Full Giga Kaleidoscope Backtest The Full Giga Kaleidoscope Backtest module enables users to backtest Full GKD Long and Short signals, allowing the creation of a comprehensive NNFX trading system consisting of two confirmation indicators, a baseline, a measure of volatility/volume, and continuations. This module offers two types of backtests: Trading and Full. The Trading backtest allows users to evaluate individual Long and Short trades one by one. On the other hand, the Full backtest enables the analysis of Longs or Shorts separately by toggling between them in the settings, providing insights into the results for each signal type. The Trading backtest simulates actual trading conditions, while the Full backtest evaluates all signals regardless of their Long or Short nature. Additionally, the backtest module allows testing with 1 to 3 take profits and 1 stop loss. The Trading backtest supports 1 to 3 take profits, while the Full backtest is limited to 1 take profit. The Trading backtest also includes a trailing take profit feature. Regarding the percentage of trade removed at each take profit, the backtest module incorporates the following predefined values: Take profit 1: 50% of the trade is removed. Take profit 2: 25% of the trade is removed. Take profit 3: 25% of the trade is removed. Stop loss: 100% of the trade is removed. After achieving each take profit, the stop loss level is adjusted accordingly. When take profit 1 is reached, the stop loss is moved to the entry point. Similarly, when take profit 2 is reached, the stop loss is shifted to take profit 1. The trailing take profit feature comes into effect after take profit 2 or take profit 3, depending on the number of take profits selected in the settings. The trailing take profit is always activated on the final take profit when 2 or more take profits are chosen. The backtest module also provides the option to restrict testing to a specific date range, allowing for simulated forward testing using past data. Additionally, users can choose to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. It is also possible to activate alerts and toggle sections of the trading panel on or off. Historical take profit and stop loss levels are displayed as overlaid horizontal lines on the chart for reference. To utilize this strategy, follow these steps: 1. GKD-B Baseline Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-B Baseline module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-B Baseline." 2. GKD-V Volatility/Volume Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-V Volatility/Volume module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-V Volatility/Volume." 3. Adjust the "Confirmation 1 Type" in the GKD-C Confirmation Indicator to "GKD New." 4. GKD-C Confirmation 1 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 1 module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation 1." 5. Adjust the "Confirmation 2 Type" in the GKD-C Confirmation 2 Indicator to "GKD New." 6. GKD-C Confirmation 2 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 2 module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation 2." 7. Adjust the "Confirmation Type" in the GKD-C Continuation Indicator to "GKD New." 8. GKD-C Continuation Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Continuation module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation." The GKD system utilizes volatility-based take profits and stop losses, where each take profit and stop loss is calculated as a multiple of volatility. Users have the flexibility to adjust the multiplier values in the settings to suit their preferences. In a future update, the Full Giga Kaleidoscope Backtest module will include the option to incorporate a GKD-E Exit indicator, completing the full trading strategy. █ Full Giga Kaleidoscope Backtest Entries Within this module, there are ten distinct types of entries available, which are outlined below: Standard Entry 1-Candle Standard Entry Baseline Entry 1-Candle Baseline Entry Volatility/Volume Entry 1-Candle Volatility/Volume Entry Confirmation 2 Entry 1-Candle Confirmation 2 Entry PullBack Entry Continuation Entry Each of these entry types can generate either long or short signals, resulting in a total of 20 signal variations. The user has the flexibility to enable or disable specific entry types and choose which qualifying rules within each entry type are applied to price to determine the final long or short signal. The following section provides an overview of the various entry types and their corresponding qualifying rules: Standard Entry 1. GKD-C Confirmation gives signal 2. Baseline agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 1-Candle Standard Entry 1a. GKD-C Confirmation gives signal 2a. Baseline agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Baseline Entry 1. GKD-B Basline gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior 1-Candle Baseline Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Volatility/Volume Entry 1. GKD-V Volatility/Volume gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Volatility/Volume Entry 1a. GKD-V Volatility/Volume gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior Next Candle 1b. Price retraced 2b. Volatility/Volume agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Baseline agrees Confirmation 2 Entry 1. GKD-C Confirmation 2 gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Volatility/Volume agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Confirmation 2 Entry 1a. GKD-C Confirmation 2 gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior Next Candle 1b. Price retraced 2b. Confirmation 2 agrees 3b. Confirmation 1 agrees 4b. Volatility/Volume agrees 5b. Baseline agrees PullBack Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price is beyond 1.0x Volatility of Baseline Next Candle 1b. Price inside Goldie Locks Zone Minimum 2b. Price inside Goldie Locks Zone Maximum 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Continuation Entry 1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously 2. Baseline hasn't crossed since entry signal trigger 4. Confirmation 1 agrees 5. Baseline agrees 6. Confirmation 2 agrees █ Volatility Types Included This module includes 17 types of volatility: Close-to-Close Parkinson Garman-Klass Rogers-Satchell Yang-Zhang Garman-Klass-Yang-Zhang Exponential Weighted Moving Average Standard Deviation of Log Returns Pseudo GARCH(2,2) Average True Range True Range Double Standard Deviation Adaptive Deviation Median Absolute Deviation Efficiency-Ratio Adaptive ATR Mean Absolute Deviation Static Percent Close-to-Close Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility. Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is. Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility. Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators. Parkinson Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day. The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility. One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator. Garman-Klass Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security. Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate. Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements. Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes. Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail. Rogers-Satchell Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero. Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending. The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions. A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail. Yang-Zhang Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error. Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator. Garman-Klass-Yang-Zhang Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation. GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator. Exponential Weighted Moving Average The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling. The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted. The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series. Standard Deviation of Log Returns This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)). Pseudo GARCH(2,2) This is calculated using a short- and long-run mean of variance multiplied by ?. ?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L) Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?. Average True Range The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period. The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges. True Range Double A special case of ATR that attempts to correct for volatility skew. Standard Deviation Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation. Adaptive Deviation By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility. Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting). The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions. Median Absolute Deviation The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant. Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution. Efficiency-Ratio Adaptive ATR Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range. Mean Absolute Deviation The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation. This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life. Static Percent Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss █ Giga Kaleidoscope Modularized Trading System Core components of an NNFX algorithmic trading strategy The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm: 1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc. 2. Baseline - a moving average to identify price trend 3. Confirmation 1 - a technical indicator used to identify trends 4. Confirmation 2 - a technical indicator used to identify trends 5. Continuation - a technical indicator used to identify trends 6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown 7. Exit - a technical indicator used to determine when a trend is exhausted What is Volatility in the NNFX trading system? In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period. True range is calculated as the maximum of the following values: -Current high minus the current low -Absolute value of the current high minus the previous close -Absolute value of the current low minus the previous close ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses. Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass What is a Baseline indicator? The baseline is essentially a moving average, and is used to determine the overall direction of the market. The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR). Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail. By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend. What is a Confirmation indicator? Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI). The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend. Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators. In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades. What is a Continuation indicator? In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy. What is a Volatility/Volume indicator? Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa. By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements. What is an Exit indicator? The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy. The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit. The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses. In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor. Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time. How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above? Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are: 1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm) 2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm) 3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm) 4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm) 5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm) (additional module types will added in future releases) Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal. That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy. This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm. What does the application of the GKD trading system look like? Example trading system: Backtest: Full Giga Kaleidoscope Backtest as shown on the chart above Baseline: Hull Moving Average as shown on the chart above Volatility/Volume: Hurst Exponent as shown on the chart above Confirmation 1: Vorext as shown on the chart above Confirmation 2: Coppock Curve as shown on the chart above Continuation: Fisher Transform as shown on the chart above Exit: Rex Oscillator Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
Стратегия Pine Script®
от loxx
5