cryptomars signal short 2.0Description:
1. In the indicator, there is an orange signal that fluctuates linearly. It is a buy signal when it goes from bottom to top. When the signal line remains in the upper position, it indicates a multi-party trend.
2. When it goes from top to bottom, it indicates a sell signal. When the signal line remains below, it indicates a sales trend.
3. Depending on the time level, when the position of the signal line changes, determine whether the current candle is completed or not according to the time level of the chart you selected to determine the signal. For example, if you select a chart level of 5 meters, then when the signal line changes, for example, it will send a sell signal from top to bottom. At this time, please do not rush to sell. You should wait for this 5 meter candlestick to complete. When the candle is over and the next candle is started, if the signal line remains in the top-down form, the sell signal is normal and you can sell it.
Because the position of the signal appears, it is the location of the sale. During the completion of the candlestick , the signal may disappear after disappearing. We only have to wait for a while to get a more stable deal.
4. The alarm setting is very simple. There are two lines in the indicator. One is the orange signal line that fluctuates up and down, and the other is the fixed zero line of “zero”.
We set it in the alarm. When the signal line passes "zero" from the top, the short signal is sent only when the candle map is completed. When the signal line passes "zero" from "up" below, the signal is sent for a long time when the candlestick is completed.
One trick, the appearance of the signal, is that the price runs in one direction for a while, so it appears at or near the bottom. Because, when we have already made a profit in the transaction, we can make a profit in advance, and we do not need to wait for the opposite signal to stop the profit and reduce the risk of profit retracement.
Because in this market, the fluctuations are very large, and the people who compete are also very fierce. What we need to do is to make every transaction as possible, and we are all profitable. If we sell and find that the price is still rising, please don't feel sorry, don't consider eating all the profits.
6. When the signal appears, in most cases, even in the impact trend, it will still run a distance in the direction of the signal, that is, you will profit, so please close the position and make a profit in time. Otherwise, when the price volatility is too small, you miss the profit point, the price starts to run in the opposite direction, and you may change from profit to loss.
BITMEX's trailing stop loss is a great feature, please use it flexibly.
7, if it is a shock trend, please try not to trade.
8. We recommend that you turn on the “cryptomars 3.0” and “cryptomars 1.0” indicators. No matter who signs the trade first, you can trade, which can help you get more profit.
9. Remember, I hope this indicator will be your powerful assistant, but please don't rely on it completely. Learning more trading knowledge and skills is even more important. Therefore, when we consider the profitable position, you can use your trading skills, MACD , KDJ, etc. to assist and profit in a more suitable position.
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cryptomars signal 3.0Description:
1. In the indicator, there is an orange signal that fluctuates linearly. It is a buy signal when it goes from bottom to top. When the signal line remains in the upper position, it indicates a multi-party trend.
2. When it goes from top to bottom, it indicates a sell signal. When the signal line remains below, it indicates a sales trend.
3. Depending on the time level, when the position of the signal line changes, determine whether the current candle is completed or not according to the time level of the chart you selected to determine the signal. For example, if you select a chart level of 5 meters, then when the signal line changes, for example, it will send a sell signal from top to bottom. At this time, please do not rush to sell. You should wait for this 5 meter candlestick to complete. When the candle is over and the next candle is started, if the signal line remains in the top-down form, the sell signal is normal and you can sell it.
Because the position of the signal appears, it is the location of the sale. During the completion of the candlestick , the signal may disappear after disappearing. We only have to wait for a while to get a more stable deal.
4. The alarm setting is very simple. There are two lines in the indicator. One is the orange signal line that fluctuates up and down, and the other is the fixed zero line of “zero”.
We set it in the alarm. When the signal line passes "zero" from the top, the short signal is sent only when the candle map is completed. When the signal line passes "zero" from "up" below, the signal is sent for a long time when the candlestick is completed.
One trick, the appearance of the signal, is that the price runs in one direction for a while, so it appears at or near the bottom. Because, when we have already made a profit in the transaction, we can make a profit in advance, and we do not need to wait for the opposite signal to stop the profit and reduce the risk of profit retracement.
Because in this market, the fluctuations are very large, and the people who compete are also very fierce. What we need to do is to make every transaction as possible, and we are all profitable. If we sell and find that the price is still rising, please don't feel sorry, don't consider eating all the profits.
6. When the signal appears, in most cases, even in the impact trend, it will still run a distance in the direction of the signal, that is, you will profit, so please close the position and make a profit in time. Otherwise, when the price volatility is too small, you miss the profit point, the price starts to run in the opposite direction, and you may change from profit to loss.
BITMEX's trailing stop loss is a great feature, please use it flexibly.
7, if it is a shock trend, please try not to trade.
8. We recommend that you turn on the “cryptomars 2.0” and “cryptomars 1.0” indicators. No matter who signs the trade first, you can trade, which can help you get more profit.
9. Remember, I hope this indicator will be your powerful assistant, but please don't rely on it completely. Learning more trading knowledge and skills is even more important. Therefore, when we consider the profitable position, you can use your trading skills, MACD , KDJ, etc. to assist and profit in a more suitable position.
T7 JNSARUpdated code for the T7 JNSAR system earlier published here -
Following updates made to the code
1. Buy / Sell arrows now appear when the corresponding conditions are met.
2. Support for Heikin-Ashi Candles added
3. Different Backtesting Position Sizing Algorithms added for evaluation
Also am republishing the trading rules here again with some modification
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Place an After Market Order @ Market Price with your broker after market close so that you get to execute the trade next trading day @ Market open to capture near similar price as the daily open price seen on the chart. This execution mode will give you the best chance to minimise the slippage and mimic the backtester results as closely as practically possible.
7. Follow all the 6 rules above religiously, as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Happy Trading !!! As always am looking out for your valuable feedback.
T7 JNSARJNSAR stands for Just Nifty Stop & Reverse. This is a trend following daily bar trading system for NIFTY. Original idea belongs to ILLANGO @ I coded the pine version of this system based on a request from @stocksonfire. Use it at your own risk after validation at your end. Neither me or my company is responsible for any losses you may incur using this system. Hope you like this system and enjoy trading it !!!
While trading this system you must follow these simple rules.
1. Go Long when the daily close is above the JNSAR line. Go Short when the daily close is below the JNSAR line. JNSAR line is the varying green line overlayed over the price chart. Once a signal comes at market close enter in the direction of the signal @ market price @ next day market open.
2. Trade only Nifty Index. This system was developed and backtested only for NIFTY Index. So trade in its Futures or Options, as you may deem fit. My recommendation is to choose futures for simplicity. If you want to reduce the trading cost and go with options, trade with deep in the money options, preferably 2 strikes far from the spot price.
3. Trade all signals. Markets trend only 30-35% of the time and hence the system is only accurate to that extend. But system tends to make enough money, in this small trending window, to keep the overall profitability in good health. But one never knows when a big trend may come and when it comes its absolutely imperative that you take it. To ensure that, trade all signals and don't be choosy about what signals you are going to trade. Also I wouldn't recommend using your own analysis to trade this system. Too many drivers will crash the car.
4. Like all trend following systems, this system will have many whipsaws during flat markets along with large trade and account drawdowns. Also some months and even years may not be profitable. But to trade this system profitably, it is necessary to take these in one's stride and keep trading. As the backtester results from 1990 to 2016 proves, this system is profitable overall thus far. Take confidence from that objective fact.
5. Initial capital that you need to have to trade one lot of NIFTY should be atleast - (Margin Money required to take and hold 1 lot position + maximum drawdown amount per lot)*1.2. Be prepared to add more if need be, but the above formula will give a rough idea of what you need to have to start trading and be in the game always.
6. Follow all the 5 rules above religiously as if your life depends on it. If you cant, then don't trade this system; You will certainly loose money.
Tight Entry Trend Engine Strategy═══════════════════════════════════════
TIGHT ENTRY TREND ENGINE
═══════════════════════════════════════
A breakout-based trend-following system designed to capture explosive
moves by entering at precise resistance/support breakouts with minimal
entry risk and massive profit potential.
⚠️ LOW WIN RATE, HIGH REWARD SYSTEM ⚠️
This is NOT a high win-rate strategy. Expect 25-35% winners, but
when it hits, winners are typically 10X+ larger than losers.
═══════════════════════════════════════
🎯 WHAT THIS SYSTEM DOES
═══════════════════════════════════════
The Tight Entry Trend Engine identifies powerful breakout opportunities
by detecting when price breaks through established trendlines with
confirmation from higher timeframe trends:
1. DYNAMIC TRENDLINE DETECTION (3 BANKS)
• Automatically draws support and resistance trendlines
• 3 separate "banks" capture short-term, medium-term, and long-term levels
• Each bank has configurable parameters (required pivot touch count,
angle limits, lengths)
2. BREAKOUT ENTRY TIMING
• Enters LONG when price breaks ABOVE resistance trendlines
• Enters SHORT when price breaks BELOW support trendlines
• Entry Alert occurs at the exact moment of breakout = "tight entry"
• Stop-loss placed just below/above the broken trendline (configurable)
3. HIGHER TIMEFRAME TREND FILTER
• Uses Hull Moving Average (HMA) on higher timeframe for trend following
• Auto-adjusts HTF based on your chart timeframe
• Optional filters prevent entries against major trend
• Optional "overextension" filter avoids buying parabolic moves
4. VOLATILITY-ADAPTIVE RISK MANAGEMENT
• Stop-loss calculated using Average True Range (ATR)
• Tighter stops = better R:R
• Profit targets adjust dynamically with volatility
• Breakeven stop moves automatically when in profit
• Extended profit targets when far from HTF trend
═══════════════════════════════════════
📊 HOW IT WORKS (METHODOLOGY)
═══════════════════════════════════════
STEP 1: TRENDLINE FORMATION
The system continuously scans for pivot highs and pivot lows to
construct trendlines. You control:
BANK 1 (Short-Term):
- Pivot Length: How many bars to look back for swing points
- Min Touches: How many pivots needed to form a line (default: 3)
- Max Length: How far back lines can reach (default: 180 bars)
- Angle Limits: Maximum steepness allowed for valid trendlines
- Tolerance: How close pivots must align to form horizontal lines
BANK 2 (Medium-Term):
- Slightly longer pivot periods for more significant levels
- Captures medium-term trend structure
- Default Max Length: 200 bars
BANK 3 (Long-Term):
- Focuses on major support/resistance zones
- Often uses horizontal levels (angled lines disabled by default)
- Default Max Length: 300 bars
The system draws RESISTANCE lines (red) above price and SUPPORT
lines (green) below price. These adapt in real-time as new pivots form.
STEP 2: BREAKOUT DETECTION
LONG SIGNALS:
- Price closes above a resistance trendline
- Higher timeframe trend is up (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
SHORT SIGNALS:
- Price closes below a support trendline
- Higher timeframe trend is down (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
The "tight" aspect: Because you're entering right at the trendline
break, your stop-loss can be placed very close (just below the
broken resistance for longs), creating exceptional risk/reward ratios.
STEP 3: POSITION SIZING
Choose between:
- Fixed $ Risk Per Trade: Risk same dollar amount every trade
- % Risk Per Trade: Risk percentage of current equity
Position size automatically calculated based on:
- Your risk amount
- Distance to stop-loss (ATR-based)
- Works with stocks, futures, crypto (auto-adjusts for contract multipliers)
STEP 4: EXIT MANAGEMENT
Multiple exit methods working together:
- PROFIT TARGET: Exits when profit reaches 100x your risk
- EXTENDED PROFIT: Earlier exit (80R) when very far from HTF trend
- STOP LOSS: Fixed ATR-based stop below entry
- HTF TREND EXIT: Exits when price crosses below HTF trend with profit
- BREAKEVEN PULLBACK: Exits if profit drops below 0.6R after reaching breakeven
- PARTIAL PROFITS: Optional - take partial profits at specified R-multiple
═══════════════════════════════════════
🔧 KEY COMPONENTS EXPLAINED
═══════════════════════════════════════
HULL MOVING AVERAGE (HMA)
A smoothed moving average that reduces lag compared to traditional
MAs. The system uses HMA on a higher timeframe to determine the
dominant trend direction. You can choose:
- Auto HTF: System picks appropriate HTF based on your chart timeframe
- Manual HTF: You specify the higher timeframe
AVERAGE TRUE RANGE (ATR)
Measures current market volatility. Used for:
- Stop-loss distance (tighter when volatility low)
- Profit targets (larger when volatility high)
- Position sizing (smaller positions in volatile conditions)
- Breakeven trigger distance
TRENDLINE ANGLE FILTERING
Each trendline bank has angle limits to ensure quality:
- Resistance lines: Max downward/upward slope allowed
- Support lines: Max downward/upward slope allowed
- Angles automatically adjust based on current volatility
- Prevents overly steep/unreliable trendlines
SENSITIVITY CONTROL
One master slider adjusts multiple parameters:
- Trendline detection sensitivity
- HTF MA length
- Exit timing
- Auto-adjusts for daily+ timeframes (60% increase)
═══════════════════════════════════════
⚙️ WHAT YOU SEE ON YOUR CHART
═══════════════════════════════════════
TRENDLINES:
✓ Red resistance lines above price
✓ Green support lines below price
✓ Orange broken lines (past breakouts)
✓ Lines extend to show current levels
HTF TREND:
✓ Thick colored line showing higher timeframe trend
✓ Color gradient: Red (bearish) → Orange → Yellow → Green (bullish)
✓ 250-bar smoothed curve for visual clarity
ENTRY/EXIT SIGNALS:
✓ Small green dot below bar = Long entry
✓ Small red dot above bar = Short entry
✓ Small red dot above = Long exit
✓ Small black dot below = Short exit
OPTIONAL DETAILED LABELS:
✓ Bank number that triggered entry (Bank 1, 2, or 3)
✓ Exit reason (Profit Target, Stop Loss, HTF Exit, etc.)
✓ Partial profit notifications
POSITION TRACKING:
✓ Yellow dashed line at entry price (extends right)
✓ Green/red fill showing current profit/loss zone
✓ Lime arrows at top = Currently in long position
✓ Red arrows at bottom = Currently in short position
✓ Gray background = No position (flat)
STATS TABLE (Top Right):
✓ Current position (LONG/SHORT/FLAT)
✓ Risk per trade ($ or %)
✓ Entry price
✓ Unrealized P/L in dollars
✓ P/L in R-multiples (how many R's profit/loss)
✓ Average winner/loser R ($ mode) OR CAGR (% mode)
═══════════════════════════════════════
📈 OPTIMAL USAGE
═══════════════════════════════════════
BEST ASSETS:
- NASDAQ:QQQ on 1-hour (reg) chart ⭐ (PRIMARY OPTIMIZATION)
- Strong trending stocks: NVDA, AAPL, TSLA, MSFT, GOOGL, AMZN
- High volatility tech stocks
- Crypto: BTC, ETH
- Any liquid asset with clear trends and momentum (GOLD)
AVOID:
- Low volatility stocks
- Ranging/choppy markets
- Penny stocks or illiquid assets
- Assets without clear directional movement
BEST TIMEFRAMES:
- PRIMARY: 1-hour charts (optimal for QQQ)
- ALSO EXCELLENT: 2H, 4H, 8H
- WORKS: 15min, 30min (only momentum leaders, more noise)
- WORKS WITH ADJUSTMENTS: 1D, 2D (decrease trendline pivot lengths)
═══════════════════════════════════════
📊 BACKTEST RESULTS (QQQ 1H (Reg hours), 1999-2024)
═══════════════════════════════════════
The system showed on NASDAQ:QQQ 1-hour timeframe (regular hours):
- Total Return: 1,100,000%+ over 24 years
- Total Trades: 500+
- Win Rate: ~20-24% (LOW - this is by design!)
- Average Winner: 8-15% gain
- Average Loser: 2-4% loss
- Win/Loss Ratio: 10:1 (winners much bigger than losers)
- Profit Factor: 3+
- Max Drawdown: 45-50%
- Risk per trade: 3% of capital
KEY INSIGHT: This is a LOW WIN RATE, HIGH REWARD system. You will
lose more trades than you win, but the few winners are so large
they more than compensate for many small losses.
IMPORTANT: These are backtested results using optimal parameters
on historical data. Real trading results will vary based on:
- Your execution and timing
- Slippage and commissions
- Your emotional discipline
- Market conditions during your trading period
═══════════════════════════════════════
🎓 WHO IS THIS FOR?
═══════════════════════════════════════
IDEAL FOR:
✓ Swing traders comfortable holding winners for longer period
✓ Part-time traders (1H = check 2-3x per day)
✓ Traders seeking exceptional risk/reward ratios
✓ Those comfortable with low win rates if winners are huge
✓ Technical analysis enthusiasts
✓ Breakout traders
✓ Trend followers
═══════════════════════════════════════
🚀 GETTING STARTED - STEP BY STEP
═══════════════════════════════════════
STEP 1: APPLY TO YOUR CHART
- Search "Tight Entry Trend Engine" in indicators
- Click to apply to your chart
- Trendlines and HTF line will appear immediately
STEP 2: CHOOSE YOUR SETTINGS
For BEGINNERS - Use These Settings First:
1. Trade Direction & Filters:
• ENABLE LONGS: ✓ ON
• ENABLE SHORTS: ✗ OFF (start with longs only)
• Sensitivity: 1.0 (default)
• HTF Trend Entry Filter: ✓ ON (safer entries)
• Block Entries When Overextended: ✓ ON (avoid parabolic tops)
2. Position Sizing & Risk:
• Position Sizing: "Per Risk"
• RISK Type: "$ Per Trade"
• Risk Amount: $200 (or 1-3% of your account)
3. Visual Settings:
• Show Support Lines: ✗ OFF (unless trading shorts)
• Show Detailed Entry/Exit Labels: ✓ ON
• Show Stats Table: ✓ ON
• Show Entry Line & P/L Fill: ✓ ON
4. Leave everything else at DEFAULT for now
STEP 3: UNDERSTAND WHAT YOU SEE
When trendlines appear:
- RED lines above = Resistance (watch for price breaking UP through these)
- GREEN lines below = Support (watch for price breaking DOWN)
- When price breaks a red line = Potential LONG entry
- When price breaks a green line = Potential SHORT entry
The HTF trend line (thick colored):
- Green/lime = Strong uptrend (favorable for longs)
- Red = Strong downtrend (favorable for shorts if enabled)
- Orange/yellow = Transitioning
STEP 4: OBSERVE SIGNALS
- Small GREEN dot below bar = System entered LONG
- Small RED dot above bar = System exited LONG
- Check the label to see which "Bank" triggered (Bank 1, 2, or 3)
- Watch the yellow entry line and colored fill show your P/L
STEP 5: PAPER TRADE FIRST
- Use TradingView's paper trading feature
- Watch how signals perform on YOUR chosen asset
- Understand the win rate will be LOW (20-35%)
- Verify that winners are indeed much larger than losers
- Test for at least 20-30 signals before going live
STEP 6: OPTIMIZE FOR YOUR ASSET (OPTIONAL)
If default settings aren't working well:
For FASTER signals (more trades):
- Reduce Pivot Length 1 to 3-4
- Reduce Max Length 1 to 120-150
- Increase Sensitivity to 1.2-1.5
For SLOWER signals (higher quality):
- Increase Pivot Length 1 to 7-10
- Increase Max Length 1 to 250+
- Decrease Sensitivity to 0.7-0.9
For DAILY timeframes:
- Increase all Pivot Lengths by 30-50%
- Increase all Max Lengths significantly
- Sensitivity: 0.6-0.8
═══════════════════════════════════════
⚙️ ADVANCED SETTINGS EXPLAINED
═══════════════════════════════════════
TRENDLINE BANK SETTINGS:
Each bank (1, 2, 3) has these parameters:
- Min Touches: Minimum pivots to form a line
- Lower (2) = More lines, earlier detection
- Higher (4+) = Fewer lines, higher quality
- Pivot Length: Lookback for swing points
- Lower (3-5) = Reacts to recent price action
- Higher (10+) = Only major swing points
- Max Length: How old a trendline can be
- Shorter (100-150) = Only recent lines
- Longer (300+) = Include historical levels
- Tolerance: Alignment strictness for horizontal lines
- Lower (3.0-3.5) = Very strict horizontal
- Higher (4.5+) = More forgiving alignment
- Allow Angled Lines: Enable diagonal trendlines
- ON = Catches sloped support/resistance
- OFF = Only horizontal levels
- Angle Limits: Maximum steepness allowed
- Lower (1-2) = Only gentle slopes
- Higher (4-6) = Accept steeper angles
- Automatically adjusts for volatility
ATR MULTIPLIERS:
- STOP LOSS ATR (0.6): Distance to stop-loss
- Lower (0.4-0.5) = Tighter stops, stopped out more
- Higher (0.8-1.0) = Wider stops, more room
- PROFIT TARGET ATR (100): Main profit target
- This is 100x your risk = 10,000% R:R
- Lower (50-80) = Take profits sooner
- Higher (120+) = Let winners run longer
- BREAKEVEN ATR (40): When to move stop to breakeven
- Lower (20-30) = Protect profits earlier
- Higher (60+) = Give more room before protecting
HIGHER TIMEFRAME:
- Auto HTF: Automatically selects appropriate HTF
- 5min chart → uses 2H
- 15-30min → uses 6H
- 1-4H → uses 2D
- Daily → uses 4D
- HTF MA Length (300): HMA period for trend
- Lower (150-250) = More responsive
- Higher (400-500) = Smoother, less whipsaw
- HTF Trend Following Exit: Exits when crossing HTF
- ON = Additional exit method
- OFF = Rely only on profit targets/stops
- HTF Trend Entry Filter: Only trade with HTF trend
- ON = Safer, fewer signals
- OFF = More aggressive, more signals
- Block Entries When Overextended: Prevents chasing
- ON = Avoids parabolic tops/bottoms
- OFF = Enter all breakouts regardless
═══════════════════════════════════════
💡 TRADING PHILOSOPHY & EXPECTATIONS
═══════════════════════════════════════
This system is built on one core principle:
"ACCEPT SMALL, FREQUENT LOSSES TO CAPTURE RARE, MASSIVE WINS"
What this means:
- You WILL lose 65%-75% of your trades
- Most losses will be small (1-2R)
- Some winners hit 80R+
- Over time, math works in your favour
TSI Base BTC 1D /tv! (www.tradingview.com)
# 🧠 TSI Base BTC 1D /tv
## Overview
**TSI Base BTC 1D /tv** is a **trend-following strategy** optimized for **Bitcoin on the 1D timeframe**, though it also performs strongly across other major cryptocurrencies.
It’s designed to identify major directional shifts while filtering out short-term noise, maintaining a balance between **clarity, consistency, and risk control**. The system focuses on staying aligned with large market trends — not chasing every fluctuation — which makes it particularly suited for traders seeking structured, high-integrity signals.
---
## Backtesting & Performance
This strategy has been tested extensively across multiple market cycles. The chosen backtest range — **from 2018 to the present** — is deliberate, as it captures both a full **bear market and bull market phase**, offering a statistically representative view of long-term performance and risk behavior.
We also recommend testing the strategy **from 2023 onward**, covering the ongoing bull run, to evaluate how it adapts to renewed momentum and volatility expansion.
Across both periods, TSI Base BTC 1D /tv demonstrates **consistent profitability**, **contained drawdowns**, and a **disciplined number of trades**, often outperforming a simple buy-and-hold benchmark.
Although primarily designed for **1D charts**, the system can also be applied to shorter timeframes while maintaining its trend-based integrity.
---
## Risk Management Inputs
The strategy includes optional parameters allowing traders to fine-tune risk and reward dynamics while preserving the same core logic:
- **Enable Stop Loss (%)** → activates a protective stop loss. You can freely adjust this percentage; however, using a **6 % Stop Loss** (as shown below) has proven to **increase overall profitability** while keeping the **maximum equity drawdown** close to **11.48 %**, compared to over 12 % without it.
📈 *Example backtest with 6 % Stop Loss enabled (2018 – 2025):*
*(Image below illustrates total P&L, drawdown, and profitable trade ratio.)*
! (<>)
- **Enable Take Profit (%)** → sets a percentage target where profits are automatically secured once reached.
- **Fixed Stop-Loss / Take-Profit Price** → allows absolute price levels (enter “0” to disable).
- **Enable Trailing Stop (%)** → locks in profits by following price movement from the last peak.
> These inputs are optional and should be used experimentally. Each trader can adapt them to their own risk tolerance and market conditions.
---
## Automation
Given its non-repainting design, **automation is highly recommended** for consistent execution.
The strategy can be connected to external automation systems such as **Signum**, which has been tested and confirmed to operate seamlessly.
*(Disclosure: we are not affiliated with Signum or any automation provider. Mentions are purely illustrative and for educational purposes.)*
---
## Trading Philosophy
TSI Base BTC 1D /tv aims to **capture the essence of macro trends** while avoiding emotional over-trading.
It keeps traders positioned during periods of strength and sidelines them during uncertainty, offering a disciplined, data-driven approach to following momentum.
---
## Key Characteristics
- ✅ **No Repainting** — signals confirmed on candle close.
- ✅ **Trend-Based Logic** — trades align with macro directional bias.
- ✅ **Volatility-Adaptive** — dynamic envelopes respond to market expansion and contraction.
- ✅ **Backtest-Proven Stability** — consistent across multiple cycles.
- ✅ **Automation-Ready** — compatible with external trade-execution platforms.
---
⚠️ **Disclaimer:**
This strategy is provided solely for **educational and research purposes**. It does **not constitute financial advice**.
Users are responsible for their own configurations, including Stop Loss, Take Profit, and Trailing Stop settings.
While examples show that enabling a **6 % Stop Loss** can improve historical results and reduce drawdown, performance may vary across assets and timeframes.
Always backtest thoroughly and use demo environments before applying live capital.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Btc and Eth 5 min winnerWhat the Strategy Does
Finding the Trend (Like Watching the Bus Move): The strategy uses special tools called Hull Moving Averages (HMAs) to figure out if Bitcoin (BTC) Ethereum (ETH) prices are generally going up or down. It looks at short-term (5 minutes) and long-term (10 minutes) price movements to make sure the “bus” (the market) is moving strongly in one direction—up for buying, down for selling.
Spotting Good Times to Jump On (Buy or Sell Signals): It looks for two types of opportunities:
Pullbacks: When the price dips a little while still moving up (like the bus slowing down but not stopping), it’s a chance to buy.
Breakouts: When the price suddenly jumps higher after being stuck (like the bus speeding up), it’s another chance to buy. It does the opposite for selling when prices are dropping.
It also checks if there’s enough “passenger activity” (volume) and momentum (speed of price change) to make sure it’s a good move.
Avoiding Traffic Jams (Filters): The strategy uses tools like RSI (to check if the market’s too fast or too slow), volume (to see if enough people are trading), and ATR (to measure how wild the price swings are). It skips trades if things look too chaotic or if the trend isn’t strong enough.
Setting Safety Stops and Profit Targets: Once you’re on the “bus,” it sets rules to protect you:
Stop-Loss: If the price moves against you by a small amount (0.5% of the typical price swing), you jump off to avoid losing too much—think of it as getting off before the bus crashes.
Take-Profit: If the price moves in your favor by a small amount (1.0% of the typical swing), you cash out—imagine getting off at your stop with a profit.
Trailing Stop: If the price keeps moving your way, it adjusts your exit point to lock in more profit, like moving your stop closer as the bus keeps going.
Using Leverage (10x Boost): This strategy uses 10x leverage on Binance futures, meaning for every $1 you have, you trade like you have $10. This can make profits (or losses) 10 times bigger, so it’s risky but can be rewarding if you’re careful.
Why 5 Minutes and Bitcoin and Ethereum?
5-Minute Chart: This is like checking the bus every 5 minutes to make quick, small trades—perfect for fast, short profits.
Bitcoin Ethereum (BTC/USD)(ETH/USD): It’s the most popular and liquid crypto, so there’s lots of activity, making it easier to jump on and off without getting stuck.
Why It Aims for 90% Wins (But Be Realistic)
The goal is to win 9 out of 10 trades by being super picky about when to trade—only jumping on when the trend, momentum, and volume are all perfect. But in real trading, markets can be unpredictable, so 90% is very hard to achieve. Still, this strategy tries to be as accurate as possible by avoiding bad moves and focusing on strong trends.
Risks for a New Trader
Leverage: Trading with 10x leverage means small price moves can lead to big losses if you’re not careful. Start with a demo account (pretend money) on TradingView or Binance to practice.
Learning Curve: This strategy uses technical terms (like HMAs, RSI) and tools you’ll need to learn over time. Don’t rush—just practice and ask questions!
How to Use It
Go to TradingView, load this strategy on a 5-minute BTC/USD futures chart on Binance.
Watch the green triangles (buy signals) and red triangles (sell signals) on the chart—they tell you when to trade.
Use the stops and targets to manage your trades—don’t guess, let the strategy guide you.
Start small, learn from each trade, and don’t risk money you can’t afford to lose.
This is like learning to ride a bike—start slow, practice, and you’ll get better. If you have more questions or want simpler tips, feel free to ask! Trading can be fun and rewarding, but it takes patience and practice.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Ultimate Stochastics Strategy by NHBprod Use to Day Trade BTCHey All!
Here's a new script I worked on that's super simple but at the same time useful. Check out the backtest results. The backtest results include slippage and fees/commission, and is still quite profitable. Obviously the profitability magnitude depends on how much capital you begin with, and how much the user utilizes per order, but in any event it seems to be profitable according to backtests.
This is different because it allows you full functionality over the stochastics calculations which is designed for random datasets. This script allows you to:
Designate ANY period of time to analyze and study
Choose between Long trading, short trading, and Long & Short trading
It allows you to enter trades based on the stochastics calculations
It allows you to EXIT trades using the stochastics calculations or take profit, or stop loss, Or any combination of those, which is nice because then the user can see how one variable effects the overall performance.
As for the actual stochastics formula, you get control, and get to SEE the plot lines for slow K, slow D, and fast K, which is usually not considered.
You also get the chance to modify the smoothing method, which has not been done with regular stochastics indicators. You get to choose the standard simple moving average (SMA) method, but I also allow you to choose other MA's such as the HMA and WMA.
Lastly, the user gets the option of using a custom trade extender, which essentially allows a buy or sell signal to exist for X amount of candles after the initial signal. For example, you can use "max bars since signal" to 1, and this will allow the indicator to produce an extra sequential buy signal when a buy signal is generated. This can be useful because it is possible that you use a small take profit (TP) and quickly exit a profitable trade. With the max bars since signal variable, you're able to reenter on the next candle and allow for another opportunity.
Let me know if you have any questions! Please take a look at the performance report and let me know your thoughts! :)
[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.
Nifty scalping 3 minutesOverview:
The "Nifty Scalping 3 Minutes" strategy is a uniquely tailored trading system for Nifty Futures traders, with a clear focus on capital preservation, dynamic risk management, and high-probability trade entries. This strategy uses unique combination of standard technical indicators like Jurik Moving Average (JMA), Exponential Moving Average (EMA), and Bollinger Bands, but it truly stands out through its Price-Volume Spike Detection system—a unique mechanism designed to trigger trades only during periods of high momentum and market participation. The strategy also incorporates robust risk management, ensuring that traders minimize losses while maximizing profits. in complete back test range max drawdown is less than 1%
Scalping Approach and Requirements:
The strategy focuses on quick in and out trades, aiming to capture small, quick profits during periods of heightened market activity. For optimal performance, traders should have ₹2,00,000 or more in capital available per trade. The dynamic lot calculation and risk controls require this level of capital to function effectively.
Small, frequent trades are the focus, and the strategy is ideal for traders comfortable with high-frequency executions. Traders with insufficient capital or those not comfortable with frequent trades may find this strategy unsuitable.
Default Properties for Publication:
Initial Capital: ₹2,000,000
Lot Size: 25 contracts (adjusted dynamically based on available margin)
Stop-Loss: Risk per trade capped at 1% of equity.
Slippage and Commission: Realistic values are factored into the backtesting.
Key Feature: Price-Volume Spike Detection
1. Condition: Trades are executed only when there is a significant price spike confirmed by a volume spike. The candle width is calculated by multiplying the price change (difference between the candle's open and close) by the volume, and this result is compared to a 126-period average of both price and volume.
A trade is triggered when the current price-volume spike exceeds this average by a preset volume multiplier (default set at 3). This ensures that both the price change and volume are unusually strong compared to normal market behavior.
2. Reasoning: Many traders fail to incorporate the relationship between price movement and volume effectively. By using this Price-Volume Spike Detection mechanism, the strategy ensures that it only enters trades during periods of strong market momentum when both price and volume confirm a real market move, not just noise or small fluctuations.
The 126-period moving average of volume is chosen specifically because it represents a complete trading session on the 3-minute chart. This ensures that the volume spike is compared against a realistic baseline of daily activity, making the detection more robust and reliable.
The volume multiplier allows flexibility in determining the threshold for a significant spike, enabling users to fine-tune the strategy according to their risk tolerance and market conditions.
Trade Placement Logic:
1. Trend Confirmation with JMA and EMA:
Condition: The strategy will only consider entering a trade when JMA crosses above EMA for a long trade or JMA crosses below EMA for a short trade.
Reasoning: The JMA is used for its low lag and responsiveness, allowing it to capture early trends, while the EMA adds a level of confirmation by weighing recent price action more heavily. This dual confirmation ensures that trades are entered only when a solid trend is in place.
2. Bollinger Bands for Volatility Breakouts:
Condition: In addition to the JMA-EMA crossover, the price must break outside the Bollinger Bands—above the upper band for long trades, or below the lower band for short trades.
Reasoning: Bollinger Bands are a volatility indicator. By requiring a price breakout beyond the bands, the strategy ensures that trades are placed during periods of high volatility, avoiding low-momentum, sideways markets.
3. Volume and Price Confirmation (Price-Volume Spike Detection):
Condition: A trade is only triggered if the price-volume spike condition is met. This ensures that the market move is backed by strong volume and that the price change is significant relative to the recent average activity.
Reasoning: This condition filters out low-volume environments where price movements are more likely to reverse or stall. By waiting for a spike in both price and volume, the strategy ensures that it enters trades during high-momentum periods, where follow-through is more likely.
Exit Logic and Risk Management:
1. Stop-Loss (SL) Placement:
Condition: Upon entering a trade, an initial stop-loss is placed below the candle low for long trades or above the candle high for short trades. This is adjusted if the risk exceeds 1% of total capital.
Reasoning: The stop-loss is placed at a logical level that accounts for recent price action, ensuring that the trade is given room to develop while protecting capital from unexpected market reversals.
2. Profit Target and Partial Profit Booking:
Condition: The first profit target is set at 2.1x the initial risk for long trades, and 2.5x the initial risk for short trades.
Reasoning: The 2.1x risk-reward ratio for long trades provides a solid return while maintaining a conservative risk profile. For short trades, the strategy uses a higher 2.5x risk-reward ratio because market falls tend to be sharper and quicker than rises, allowing for larger profit targets to be reached more reliably.
Partial Profit Booking: Once the first target is hit, 60% of the position is closed to lock in profits. The remaining 40% is left to run with a trailing stop.
3. ATR-Based Trailing Stop:
Condition: Once the first target is hit, the ATR (Average True Range) trailing stop is applied to the remaining position. This dynamically adjusts the stop-loss as the trade moves in a favorable direction.
Reasoning: The trailing stop allows the trade to capture further gains if the trend continues, while protecting profits if the momentum weakens. The ATR ensures that the stop adjusts according to the market's current volatility, providing flexibility and protection.
4. Time-Based Exit:
Condition: If a trade is still open by 3:20 PM, it is automatically closed to avoid end-of-day volatility.
Reasoning: The time-based exit ensures that trades are not held into the often-volatile closing minutes of the market, reducing the risk of unexpected price swings.
Capital and Risk Management:
1. Lot Size Calculation:
Condition: The strategy calculates the number of lots dynamically based on the available margin. It uses only 10% of total equity for each trade, and ensures that the maximum risk per trade does not exceed 1% of total capital.
Reasoning: This ensures that traders are not over-leveraged and that the risk is controlled for each trade. Capital protection is at the core of the strategy, ensuring that even during adverse market conditions, the trader’s capital is preserved.
2. Stop-Loss Protection:
Condition: The stop-loss is designed to ensure that no more than 1% of capital is at risk in any trade.
Reasoning: By limiting risk exposure, the strategy focuses on long-term capital preservation while still allowing for profitable trades in favorable market conditions.
STBT/BTST Facilitation:
1. Feature: The strategy allows traders the option to hold positions overnight, facilitating STBT (Sell Today Buy Tomorrow) and BTST (Buy Today Sell Tomorrow) trades.
Reasoning: Backtests show that holding positions overnight when all trade conditions are still valid can lead to beneficial outcomes. This feature allows traders to take advantage of overnight market movements, providing flexibility beyond intraday trades.
Why This Strategy Stands Out:
Price-Volume Spike Detection: Unlike traditional strategies, this one uniquely focuses on Price-Volume Spike Detection to filter out low-probability trades. By ensuring that both price and volume spikes are present, the strategy guarantees that trades are placed only when there is significant market momentum.
Risk Management with Capital Protection: The strategy strictly limits the risk per trade to 1% of capital, ensuring long-term capital preservation. This is especially important for traders who wish to avoid large drawdowns and prefer a sustainable approach to trading.
2.5x Risk-Reward for Short Trades: Recognizing the sharpness of market declines, the strategy employs a 2.5x risk-reward ratio for short trades, maximizing profits during bearish trends.
Dynamic Exit Strategy: With partial profit booking and ATR-based trailing stops, the strategy is designed to capture gains efficiently while protecting capital through dynamic exit conditions.
Summary of Execution:
Entry: Triggered when JMA crosses EMA, combined with Bollinger Band breakouts and Price-Volume Spike Detection.
Capital Management: Trades are executed with 10% of available capital, and the risk per trade is capped at 1%.
Exit: Trades exit when stop-loss, ATR trailing stop, or time-based exit conditions are met.
Profit Booking: 60% of the position is closed at the first target, with the remainder trailed using an ATR-based stop.
BTC 5 min SHBHilalimSB A Wedding Gift 🌙
What is HilalimSB🌙?
First of all, as mentioned in the title, HilalimSB is a wedding gift.
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
What is BTC 5 min ☆SHB Strategy🌙?
BTC 5 min ☆SHB Strategy is a strategy supported by the HilalimSB algorithm created by the creator of HilalimSB. It automatically opens trades based on the data it receives, maintaining trades with its uniquely defined take profit and stop loss levels, and automatically closes trades when necessary. It stands out in the TradingView world with its unique take profit and stop loss markings. BTC 5 min ☆SHB Strategy is close to users' initiatives and is a strategy suitable for 5-minute trades and scalp operations developed on BTC.
What does the BTC 5 min ☆SHB Strategy target?
The primary goal of BTC 5 min ☆SHB Strategy is to close trades made by traders in short timeframes as profitably as possible and to determine the most effective trading points in low time periods, considering the commission rates of various brokerage firms. BTC 5 min ☆SHB Strategy is one of the rare profitable strategies released in short timeframes, with its useful interface, in addition to existing strategies in the markets. After extensive backtesting over a long period and achieving above-average success, BTC 5 min ☆SHB Strategy was decided to be released. Following the completion of test procedures under market conditions, it was presented to users with the unique visual effects of ☆SB.
BTC 5 min ☆SHB Strategy and Heikin Ashi
BTC 5 min ☆SHB Strategy produces data in Heikin-Ashi chart types, but since Heikin-Ashi chart types have their own calculation method, BTC 5 min ☆SHB Strategy has been published in a way that cannot produce data in this chart type due to BTC 5 min ☆SHB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way. Heikin-Ashi chart types, especially in short time intervals, carry significant risks considering the unique calculation methods involved. Thus, the possibility of being misled by the coder and causing financial losses has been completely eliminated. After the necessary conditions determined by the creator of BTC 5 min ☆SHB are met, BTC 5 min ☆SHB Heikin-Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation.
Key Features:
+HilalimSHB Algorithm: This algorithm uses a dynamic ATR-based trend-following mechanism to identify the current market trend. The strategy detects trend reversals and takes positions accordingly.
+Heikin Ashi Compatibility: The strategy is optimized to work only with standard candlestick charts and automatically deactivates when Heikin Ashi charts are in use, preventing false signals.
+Advanced Chart Enhancements: The strategy offers clear graphical markers for buy/sell signals. Candlesticks are automatically colored based on trend direction, making market trends easier to follow.
Strategy Parameters:
+Take Profit (%): Defines the target price level for closing a position and automates profit-taking. The fixed value is set at 2%.
+Stop Loss (%): Specifies the stop-loss level to limit losses. The fixed value is set at 3%.
The shared image is a 5-minute chart of BTCUSDC.P with a fixed take profit value of 2% and a fixed stop loss value of 3%. The trades are opened with a commission rate of 0.063% set for the USDT trading pair on Binance.🌙
Strategic Multi-Step Supertrend - Strategy [presentTrading]The code is mainly developed for me to stimulate the multi-step taking profit function for strategies. The result shows the drawdown can be reduced but at the same time reduced the profit as well. It can be a heuristic for futures leverage traders.
█ Introduction and How it is Different
The "Strategic Multi-Step Supertrend" is a trading strategy designed to leverage the power of multiple steps to optimize trade entries and exits across the Supertrend indicator. Unlike traditional strategies that rely on single entry and exit points, this strategy employs a multi-step approach to take profit, allowing traders to lock in gains incrementally. Additionally, the strategy is adaptable to both long and short trades, providing a comprehensive solution for dynamic market conditions.
This template strategy lies in its dual Supertrend calculation, which enhances the accuracy of trend detection and provides more reliable signals for trade entries and exits. This approach minimizes false signals and increases the overall profitability of trades by ensuring that positions are entered and exited at optimal points.
BTC 6h L/S Performance
█ Strategy, How It Works: Detailed Explanation
The "Strategic Multi-Step Supertrend Trader" strategy utilizes two Supertrend indicators calculated with different parameters to determine the direction and strength of the market trend. This dual approach increases the robustness of the signals, reducing the likelihood of entering trades based on false signals. Here is a detailed breakdown of how the strategy operates:
🔶 Supertrend Indicator Calculation
The Supertrend indicator is a trend-following overlay on the price chart, typically used to identify the direction of the trend. It is calculated using the Average True Range (ATR) to ensure that the indicator adapts to market volatility. The formula for the Supertrend indicator is:
Upper Band = (High + Low) / 2 + (Factor * ATR)
Lower Band = (High + Low) / 2 - (Factor * ATR)
Where:
- High and Low are the highest and lowest prices of the period.
- Factor is a user-defined multiplier.
- ATR is the Average True Range over a specified period.
The Supertrend changes its direction based on the closing price in relation to these bands.
🔶 Entry-Exit Conditions
The strategy enters long positions when both Supertrend indicators signal an uptrend, and short positions when both indicate a downtrend. Specifically:
- Long Condition: Supertrend1 < 0 and Supertrend2 < 0
- Short Condition: Supertrend1 > 0 and Supertrend2 > 0
- Long Exit Condition: Supertrend1 > 0 and Supertrend2 > 0
- Short Exit Condition: Supertrend1 < 0 and Supertrend2 < 0
🔶 Multi-Step Take Profit Mechanism
The strategy features a multi-step take profit mechanism, which allows traders to lock in profits incrementally. This is achieved through four user-configurable take profit levels. For each level, the strategy specifies a percentage increase (for long trades) or decrease (for short trades) in the entry price at which a portion of the position is exited:
- Step 1: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent1 / 100)
- Step 2: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent2 / 100)
- Step 3: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent3 / 100)
- Step 4: Exit a portion of the trade at Entry Price * (1 + Take Profit Percent4 / 100)
This staggered exit strategy helps in locking profits at multiple levels, thereby reducing risk and increasing the likelihood of capturing the maximum possible profit from a trend.
BTC Local
█ Trade Direction
The strategy is highly flexible, allowing users to specify the trade direction. There are three options available:
- Long Only: The strategy will only enter long trades.
- Short Only: The strategy will only enter short trades.
- Both: The strategy will enter both long and short trades based on the Supertrend signals.
This flexibility allows traders to adapt the strategy to various market conditions and their own trading preferences.
█ Usage
1. Add the strategy to your trading platform and apply it to the desired chart.
2. Configure the take profit settings under the "Take Profit Settings" group.
3. Set the trade direction under the "Trade Direction" group.
4. Adjust the Supertrend settings in the "Supertrend Settings" group to fine-tune the indicator calculations.
5. Monitor the chart for entry and exit signals as indicated by the strategy.
█ Default Settings
- Use Take Profit: True
- Take Profit Percentages: Step 1 - 6%, Step 2 - 12%, Step 3 - 18%, Step 4 - 50%
- Take Profit Amounts: Step 1 - 12%, Step 2 - 8%, Step 3 - 4%, Step 4 - 0%
- Number of Take Profit Steps: 3
- Trade Direction: Both
- Supertrend Settings: ATR Length 1 - 10, Factor 1 - 3.0, ATR Length 2 - 11, Factor 2 - 4.0
These settings provide a balanced starting point, which can be customized further based on individual trading preferences and market conditions.
Pullback_Power [JackTz]Welcome to Pullback_Power
Pullback_Power is a scalping strategy designed to capitalize on market retracements while incorporating unique dynamic features to enhance profitability.
Calculation
Pullback_Power purely uses moving averages to calculate both entry and exits. Exits can also be set to fixed percentages for both take profit and stop loss.
How the Strategy Works
Statistics show that markets normally do a recovery after each drop. Crypto markets can easily drop up to 20% within a few hours and then do a complete or partial recovery. Pullback_Power utilizes this known pattern alongside pyramiding. The strategy aims to catch one or more entries when the price drops, hoping to make profits when the market recovers from the drop. The fixed take profit and stop loss can be used to define your risk management, while the dynamic exit opportunity is riskier but provides the ability to stay in the trade longer while it recovers. Pullback_Power can make up to four entries. This means it utilizes pyramiding to spread out the entry points, but every exit is a full exit. It is not possible to partially exit.
Utility
Pullback_Power is a scalping strategy suitable for traders who operate with small trades and don't want to stay in the market for too long. Pullback_Power offers precise signals with no repainting. The strategy thrives in volatility, so crypto pairs might yield the best results, although this strategy can be adapted to work on all pairs and markets.
How to Automate It
Pullback_Power utilizes the standard placeholders of strategies on TradingView. This enables the trader to add every data point into a webhook, making it fully flexible to suit every trader's needs. To automate, create an alert, set the webhook URL, and add the JSON body needed for the webhook. An example of a simple JSON webhook with some of the standard strategy placeholders:
{
"side": "{{strategy.order.action}}",
"symbol": "{{ticker}}",
"amount": "{{strategy.order.contracts}}"
}
Read about all the standard placeholders that you can use here: TradingView - Standard strategy placeholders
Originality
Pullback_Power is unique in its ability to create precise signals without repainting while maintaining a solid approach to the pullback strategy. Its simplicity not only makes the strategy easy to use and understand but also highly effective. The simplicity reduces inputs, eliminating overfitting and limits each input to avoid incorrect usage. Many times, default settings are enough to achieve good backtesting results on almost all pairs available. Pullback_Power also differs from many other strategies by its solid code, which enhances performance and provides more reliable backtesting. The clean code increases the resilience and precision of the entries, making it less prone to errors.
Many pullback/scalping strategies normally only works on specific scopes of timeframes or pairs. Pullback_Power can easily be adapted to work on almost every scenario. The biggest change needed is the length of the moving average. The lower the timeframe, the higher a length is needed for proper results. I.e. on a 2H timeframe a length of 3 can yield good results. On a 5min timeframe the length might need to be as high as 70.
How to Use
To use Pullback_Power, add the script to your trading chart. By default, Pullback_Power opens four orders to optimize trade opportunities with a default fee value set at 0.1%. You can change these default settings in the Settings window under the Properties tab. To tailor Pullback_Power to your individual trading style, navigate to the Settings under the Input tab. Here you can configure various inputs to fit your trading style.
- Backtest settings , Start Date:
Defines the date of when the calculation starts. Use this to set the date of when the first trade could potentially emit.
- Backtest settings , End Date:
Defines the date of when the calculation ends. If there are any open trades after this date the close calculations are still live. It only makes sure that new orders cannot be opened after this date.
- Backtest settings , Only trade on weekdays:
This is a toggle you can enable or disable. If enabled it only allows new entries to happen during the normal week days, meaning Monday, Tuesday, Wednesday, Thursday and Friday.
Disable this to enable the script to open trades on all 7 days of the week.
- Open settings , Use dynamic long positions:
This toggle allows you to enable or disable the pullback level calculations after first trade.
If enabled, the calculations of level 2, 3 and 4 continues to happen after each bar, making the levels follow the price with the moving averages calculations.
If disabled, the calculations of the levels stop after the first trade. This means that the levels calculation at the point of the first trade stay fixed until all trades are closed.
You can see the difference of the green lines on the chart when you toggle this flag.
- Open settings , Data type:
This is the bar data used for the moving average calculation when opening trades. The possible data types are Open, High, Low, Close, HL2, HLC3, OHLC4, OC2 and HC2.
- Open settings , Source type:
This is the source used to calculate the moving average. The types available are: SMA, PCMA, EMA, WMA, DEMA, ZLEMA and HMA.
- Open settings , Length:
This is the length used for the moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Open settings , Offset:
This defines if the calculation should use an offset for the historical data. This does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Leverage settings , Leverage liquidation (1-125):
The script itself does not handle any custom leverage calculation – this must be done in the Properties tabs and increasing the order size.
This setting is made to test a possible liquidation event if using leverage.
By setting this to higher than 1, a red line is visible after the first trade on the chart. This indicates the liquidation price.
If this setting is set to 25, the script will calculate the liquidation price from a x25 leverage. If this price is hit, the scripts stops emitting any orders and the background turns red.
You can use this to test if your settings could handle a certain level of leverage.
- Pullback settings , Pullback 1, 2, 3 and 4:
Each of these settings defines the entry price of each pullback level. If Pullback 1 is set to -6 it means that the moving average calculation should be 6% lower than the actual price.
The same logic applies to Pullback 2, 3 and 4.
Setting any level to 0 will disable the level – eliminating any orders to emit on that level.
This can be used to change the level of pyramiding down from 4 if needed.
If you do this, remember to also change the order size and the pyramiding value in the Properties tab accordingly.
- Close settings , Use dynamic TP and SL:
If enabled, script will exit all orders using the same but separate algorithm for moving averages. This enables the user to define if you want the orders to be closed if the price level of this moving average is hit. The price level for this calculation is visible on the chart by the blue line.
Although you can change the length and offset, as described underneath, this calculation uses the same data and source type defined in the Open settings area.
- Close settings , Length, Close:
This is the length used for the closing moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Close settings , Offset, Close:
This defines if the calculation for the closing moving average should use an offset for the historical data. Just as the offset used for opening order, this does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Close settings , Use TakeProfit:
This toggle enables/disables a fixed take profit percentage.
- Close settings , TP %:
This sets the wanted % to reach on a take profit. This setting is ignored if the toggle above is disabled.
- Close settings , Use StopLoss:
This toggle enables/disables a fixed stop loss percentage.
- Close settings , SL %:
This sets the wanted % to reach on a stop loss. This setting is ignored if the toggle above is disabled.
Exit on Same Bar as Entry
By default, the script doesn't emit any exit orders on the same bar as the first entry order. Enable "Recalculation: After order is filled" to change this behavior.
Troubleshooting
While Pullback_Power is designed to provide reliable trading signals, you may encounter rare issues. One such issue could be receiving an error message stating "can't open orders with 0 or negative qty." If you encounter this error, it is likely due to specific conditions on the selected timeframe. To resolve this issue, change the timeframe on your trading chart.
Underlying Principles and Value Proposition
Pullback_Power leverages moving averages and volatility behavior to identify market retracements and capitalize on them. The strategy is rooted in the understanding that markets often experience temporary reversals or "pullbacks" before resuming their primary trend. By identifying these pullbacks and entering trades at opportune moments, Pullback_Power aims to capture quick profits from short-term market movements.
The dynamic and fixed calculations of Take Profit (TP) and Stop Loss (SL) levels enhances risk management, ensuring that potential losses are controlled while allowing room for profits to grow. The adaptive approach using the moving averages considers current market conditions, making the strategy flexible and responsive to changing volatility.
Moreover, Pullback_Power's non-repainting nature ensures the reliability of its signals, eliminating hindsight bias and providing traders with actionable insights based on real-time market data.
The strategy's simplicity and effectiveness make it accessible for traders of all experience levels. Whether you're a beginner looking to start scalping or an experienced trader seeking to diversify your trading approach, Pullback_Power offers a balanced blend of simplicity and sophistication to help you navigate the markets with confidence.
By focusing on clear, transparent principles and offering practical tools for risk management, Pullback_Power aims to provide tangible value to traders, empowering them to make informed decisions and optimize their trading outcomes.
Thank you for choosing Pullback_Power. I wish you successful trading!
Self Optimizing PSAR [Starbots]Self Optimizing Parabolic SAR Strategy (non-repainting)
Strategy constantly backtest 169 different combinations of Parabolic SAR indicator for maximum profitability and trades based on the best performing combination at that time.
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# Parabolic SAR (PSAR)
Parabolic SAR is a time and price technical analysis tool created by J. Welles Wilder and it's primarily used to identify points of potential stops and reverses. In fact, the SAR in Parabolic SAR stands for "Stop and Reverse". The indicator's calculations create a parabola which is located below price during a Bullish Trend and above Price during a Bearish Trend.
You can read more about this indicator here:
www.tradingview.com
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The logic of self - optimizing:
This script is always backtesting 169 different combinations of Parabolic SAR settings in the background and saves the net. profit gained for every single one of them, then strategy selects and use the best performing combination of settings currently available for you to trade.
It's recalculating on every bar close - if one of the parameters starts performing better than others - have a higher net profit gain (it's literally like running 169 backtests with different settings) strategy switches to that parameter and continues trading like that until one of the other indicator parameters starts performing better again and switches to that settings.
We are optimizing our strategy based on 13 different 'Increment' factors of PSAR. We keep the 'Start' factor (default 0.02) and 'Max Value' factor (default 0.2) at default for all of them.
According to creator of this indicator J. Welles Wilder, we usually want to change only 'Increment' factors of PSAR in the calculation and leave the rest at default and that's what we do, we are changing only 'Increment' input.
Inputs : (you don't need to change them at all, it's a good balance for fast and slow detection of trends on PSAR)
Start = 0.02
Max value = 0.2
Increment1 = 0.005, Increment2 = 0.01, Increment3 = 0.015
Increment4 = 0.02, Increment5 = 0.025, Increment6 = 0.03
Increment7 = 0.035, Increment8 = 0.04, Increment9 = 0.045
Increment10 = 0.05, Increment11 = 0.055, Increment12 = 0.06
Increment13 = 0.065
PSAR buy / sell conditions looks like this:
PSAR1 = start 0.02, max value 0.2, increment1 0.005
PSAR2 = start 0.02, max value 0.2, increment2 0.01
PSAR3 = start 0.02, max value 0.2, increment3 0.015
PSAR4 = start 0.02, max value 0.2, increment3 0.02
...
PSAR13 = start 0.02, max value 0.2, increment13 0.065
Backtester in the background works like this:
backtest buying PSAR1 settings with selling PSAR1 settings => save net. profit
backtest buy PSAR1 with sell PSAR2 ;
backtest buy PSAR1 with sell PSAR3 ;
backtest buy PSAR1 with sell PSAR4 ;
..........
backtest buy PSAR1 with sell PSAR13 ;
..........
backtest buy PSAR13 with sell PSAR1 ;
backtest buy PSAR13 with sell PSAR2 ;
......
backtest buy PSAR13 with sell PSAR13 ;
=>
It will backtest 16x16=169 different PSAR settings and save their profits.
Your strategy then trades based on the best performing (highest net.profit) PSAR Setting currently available. It will check the calculations and backtest them on every new bar close - it's like running 169 strategies at time, and manually selecting the best performing one.
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If you wish to use it as INDICATOR - turn on 'Recalculate after every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
Strategy example is backtested on Daily chart of SHIBUSDT Binance
All settings at default. (1000 capital, 100 order size, 0.1% fee, 1 tick slippage)
Settings:
-Start = default Parabolic SAR setting is 0.02
-Max Value = default Parabolic SAR setting is 0.2
--Recommended PSAR Increment settings:
0.02 is default, higher timeframes usually performs good on the faster Increment factors 0.03-0.05+, smaller timeframes on slow Increment factors 0.005-0.02. I recommend you the most common and logical 13 different Increment factors for optimizing in the strategy as default already (from 0.005 to 0.065 - strategy will then optimize and trade based on the most profitable combination).
- Noise-Intensity Filter 🐎0.00-0.20%🐢
This will punish the tiny trades made by certain combinations and give more advantage to big average trades. It's basically like fee calculation, it will deduct 0.xx% fee from every trade when optimizing on their backtests.
You will usually want to have it around 0.05-0.10% like your fees on exchange.
-> 🐎Less than <0.10% allows strategy to be VERY SENSITIVE to market. (a lot of trades - quick buy-sell changes)
-> 🐢More than >0.10% will slow down the strategy, it will be LESS SENSITIVE to market volatility. (less trades - slowly switches the trend direction from buy to sell)
Close Trades on Neutral
After a lot of Trades, Algo starts developing self-intelligence. It can also have a neutral score. (Grey Plots). Sell when the strategy is neutral.
Other settings:
-Take Profit, Multiple Take Profit, Trailing Take Profit, Stop Loss, Trailing Stop Loss with functional alerts.
-Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
- Strategy is trading on the bar close without repaint. You can trade Long-Sell/Short Sell or Long-Short both directions. Alerts available, insert webhook messages in the inputs.
- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
- Notes window : add your custom comments in here or save your webhook message text inside here for later use. I find this helpful to save texts inside.
Recommended TF : 4h, 8h, 1d (Trend Indicators are good at detecting directions of the market, but we can have a lot of noise and false movements on charts, you want to avoid that and ride the long term movements)
This script is fairly simple to use. It's self-optimizing and adjusting to the markets on the go.
Contrarian DC Strategy - w Entry SL Pause and TrailingStopDonchian Channel Setup:
The strategy uses a tool called the Donchian Channel. Imagine this as two lines (bands) on a chart that show the highest and lowest prices over a certain number of past trading days (default is 20 days).
There's also a centerline, which is the average of these two bands.
Entry Conditions for Trades:
Buying (Going Long): The strategy considers buying when the price touches or falls below the lower band of the Donchian Channel. However, this only happens if there has been a pause after a previous losing trade. This pause is a number of candles where no new trades are taken.
Selling (Going Short): Similarly, the strategy considers selling when price reaches or exceeds the upper band of the Donchian Channel. Again, this is subject to a pause after a losing trade.
Stop Loss and Take Profit:
Each trade has a "Stop Loss" and "Take Profit" set. The Stop Loss is a preset price level where the trade will close to prevent further losses if the market moves against your position. The Take Profit does the same but locks in profit if the market moves in your favor.
The Stop Loss is set based on a percentage of the price at which you entered the trade.
The Take Profit is determined by the Risk/Reward Ratio. This ratio helps balance how much you're willing to risk versus the potential reward.
Trailing Stop Loss:
When a trade is profitable, the strategy should involve a "Trailing Stop Loss." This means the Stop Loss level moves (or trails) the price movement to lock in profits as the market moves in your favor.
For a buy trade, if the price moves above the centerline of the Donchian Channel, the Trailing Stop Loss should be adjusted in the middle between the entry price and the centerline. Viceversa for a sell trade, it should be adjusted in the same way if the price goes below the centerline.
IMPORTANT: There's no allert for the trailing stop at the moment.
Post-Stop Loss Pause:
If a trade hits the Stop Loss (i.e., it's a losing trade), the strategy takes a break before opening another trade in the same direction. This pause helps to avoid entering another trade immediately in a potentially unfavorable market.
In summary, this strategy is designed to make trades based on the Donchian Channel, with specific rules for when to enter and exit trades, and mechanisms to manage risk and protect profits. It's contrarian because it tends to buy when the price is low and sell when the price is high, which is opposite to what many traders might do.
Broadview Algorithmic StudioWelcome! This is the writeup for the Broadview Algorithmic Studio.
There are many unique features in this script.
- Broadview Underpriced & Overpriced
- Broadview Blackout Bollinger Bands
- Trailing Take Profit Suite
- Algorithmic Weights
- VSA Score
- Pip Change Log
- Activation Panel
- Weight Scanner
There are 116 primary inputs that allow users to algorithmically output unique DCA signal-sets. There are 85 inputs that allow users to control individual lengths, levels, thresholds, and multiplicative weights of the script. You will not find any other script with this many inputs, properly strung together for you to produce unlimited strategies for any market. The entire premise for the Broadview Algorithmic Studio is for users to be able to have extensive-cutting-edge features that allow them to produce more strategies, having control over every element that outputs a signal set. The number of unique strategies you can output with this script is VAST, and each continues to follow a safe DCA methodology.
This script is ready for use with 3Commas, interactive brokers, and other means of automation. It provides detailed information on Base Orders and Safety Orders, giving the number, cumulative spending, position average, and remaining balance for each SO in the series. Using this script we will explore the depths of strategic volume scaling, and the algorithms we use to determine spending.
Let me first start by saying the number of safe DCA-friendly signal-sets this script can output is absolutely staggering.
Let's limit the scope just to the Broadview Underpriced & Overpriced and Broadview Dominance indicators.
Each band of the Dominance Suite can be controlled individually with unique lengths, levels, and weights. This means the Dominance Suite can establish Bearish or Bullish dominance, in any market condition, and give it a unique overloading weight. The Broadview Underpriced & Overpriced indicator finally gives us the ability to establish these "market conditions" first with cycles. Of all the cycles this indicator establishes, the two primary are Underpriced & Overpriced. We determine this using a composite Overbought & Oversold with an Exponential Moving Average. So the script can now know, what cycle it is in, who is dominant during that cycle, and exactly how much weight in volume scaling the order should have.
Brand new is the ability for indicators of this level to be able to talk together in a single script. The Broadview Underpriced & Overpriced indicator and the Broadview Dominance indicator can inform one another across multiple vectors, create a unique market snapshot, and give that snapshot a unique weight every bar. The unique weight is compiled in the volume scaling math, thus giving us an automated-strategic-safe and quite efficient volume scaling for every order. In our coming updates we will explore this synergy to its very deepest layers. These indicators can be laced together in many ways, called vectors.
Only in the Algorithmic Studio do we explore these depths and yield those findings, features, and inputs to the user.
Let me take a quick break to explain another area-of-opportunity for our research and development.
The VSA Score is something we've tried before, but until the creation of the Broadview Blackout Bollinger Bands Auto Indicator it was not possible. The concept we want to explore is "Positional Honing". Over time we want users and the script itself to be able to understand the difference between a script-config that produces a high number of Hits, from a configuration that produces a high number of "Misses". The Volume Scaling Accuracy Score uses the BBB Auto Indicator as a heavily reliable, non-repainting, method of determining what the very-best signals for increased volume-scaling are.
Increased volume scaling is denoted by the near-white highlighter line running vertically. This line will either fall inside the BBB Auto Indicator bands (which are hidden), or, they will fall below and outside the BBB Auto bands. If increased spending happens inside the bands it's a "Miss". If increased spending happens below and outside the bands, it's a Hit. Oftentimes misses are actually pretty good spots for extra spending, which helps lower your position average, but Hits are always better. The Hits that the BBB Auto Indicator provides are extremely good.
Let's talk about the Trailing Take Profit Suite. This suite allows us to set a trailing take profit which is a feature that lets one maximize their profits. If the trailing take profit is engaged, then when the regular take profit is hit, it will trigger, denoted in red vertical lines, and the trailing take profit will look for a specified rate of change before it actually takes profit. This usually helps traders in those times when their regular take profit was set too low, allowing them to maximize their profits with a Trailing Take Profit.
For the moment, let's think about our scores. In the dashboard you'll notice a score beginning the Pip Change Log, the VSA Score, and the Activation Panel.
These scores use a new kind of logistic correlation formula where 4 digits are given to activation, rather than 1. This is to allow room for a future concept in AI we call "Deadzones" or you can think of it as impedance. This is not a bias in logistic regression. It's an entirely different concept. A neuron, which a perceptron attempts to mimic, has a bias.. but it also has a sort of electrical resistance. This is because a neuron is individually-alive entity. So a perceptron, as it were, would need to have both a bias and a natural resistance, or deadzone.
It is a lot of fun to watch the scores and how they react during playback. They tend to smooth trends but are also quite quick to correct to accuracy. In the future we will add the deadzones and biases to the scores. This should help both users and the script produce better signal sets. The Pip Change Log is an indicator that measures Rate of Change in Pips. This is one that I am particularly excited to study, as I am a huge fan of ROC. The Activation Panel shows these scores for 4 primary indicators: On Balance Volume, Relative Strength Index, Average Directional Index, and Average True Range.
Having the Pip Change Log, VSA Score, and Activation Panel up on the dashboard with their logistic correlation scores allows traders to study markets and setups quite intimately. The weight scanner at the bottom allows users to track the cumulative applied multiplicative weights during playback. The massive number of inputs, connected vectors of indicators, input-weights, lengths, levels, and thresholds sets up all the algorithmic infrastructure for powerusers to explore every idea and strategy output they could imagine. Also with the connected vector infrastructure we can deepen our indicators in a way where, "How they talk to each other.", comes first in every development conversation.
The Algorithmic Studio is for the Power-user.
These are not basic equations coming together to determine spending. This is a massive multi-layered-perceptron with everything from Trailing-Take-Profits to strategic-automatic algorithmic downscaling. The Broadview Algorithmic Studio gives a home to the poweruser who wants access to everything in a trading and investing AI, right up until the backpropagation. The Broadview Algorithmic Studio, gives users the ability to sit in the chair of the would-be AI.
Thank you.
Good Mode RSI v2► Description:
"Good Mode RSI v2" is a powerful trading strategy designed to provide informed trading decisions. This script utilizes the popular RSI (Relative Strength Index) indicator to identify potential buying and selling opportunities in the market. It goes beyond the traditional use of RSI by incorporating carefully selected parameters to enhance its effectiveness. The strategy stands out for its customized combination of RSI levels and stop-loss/take-profit thresholds, allowing for precise trade entries and exits while effectively managing risk.
► How to Use:
To utilize the "Good Mode RSI v2" strategy, follow these steps:
1. Apply the script to your desired trading instrument and timeframe in TradingView.
2. Monitor the chart for trade signals generated by the strategy.
3. When the RSI reaches the sell level of 96, a sell signal is generated. Consider placing a sell order to take advantage of potential downward price movements.
4. take-profit level at 60 to secure profits in a strong downtrend.
5. When the RSI drops below the buy level of 4, a buy signal is generated. Consider placing a buy order to enter the market at a favorable price.
6. take-profit level at 30 to secure profits in a strong uptrend.
7. Monitor the RSI indicator on the chart to stay updated on its current value and anticipate potential trade signals.
Please note that trading decisions should be made based on a comprehensive analysis of multiple factors, including market conditions, trend analysis, and risk management. The "Good Mode RSI v2" strategy can serve as a valuable tool in your trading journey, but it should be used in conjunction with your own research and analysis.
► About it:
The "Good Mode RSI v2" strategy is not a mere replication or slight modification of existing strategies or indicators. It has been carefully crafted to provide traders with an original and purposeful approach to trading using the RSI indicator. The strategy's unique configuration of RSI levels and stop-loss/take-profit thresholds allows for improved performance and profitability. Backtesting results have shown impressive metrics, including a gain factor of 2.445 and a compelling profitability of 78.07% during the testing period.
► Referrals:
If you have any questions or need further assistance with the "Good Mode RSI v2" strategy, feel free to ask. Good luck with your trading endeavors!
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
Range BreakerStrategy Description: Range Breaker
The Range Breaker strategy is a breakout trading strategy that aims to capture profits when the price of a financial instrument moves out of a defined range. The strategy identifies swing highs and swing lows over a specified lookback period and enters long or short positions when the price breaks above the swing high or below the swing low, respectively. It also employs stop targets based on a percentage to manage risk and protect profits.
Beginner's Guide:
Understand the concepts:
a. Swing High: A swing high is a local peak in price where the price is higher than the surrounding prices.
b. Swing Low: A swing low is a local trough in price where the price is lower than the surrounding prices.
c. Lookback Period: The number of bars or periods the strategy analyzes to determine swing highs and swing lows.
d. Stop Target: A predetermined price level at which the strategy will exit the position to manage risk and protect profits.
Configure the strategy:
a. Set the initial capital, order size, commission, and pyramiding as needed for your specific trading account.
b. Choose the desired lookback period to identify the swing highs and lows.
c. Set the stop target multiplier and stop target percentage as desired to manage risk and protect profits.
Backtest the strategy:
a. Set the backtest start date to analyze the strategy's historical performance.
b. Observe the backtesting results to evaluate the strategy's effectiveness and adjust the parameters if necessary.
Implement the strategy:
a. Apply the strategy to your preferred financial instrument on the TradingView platform.
b. Monitor the strategy's performance and adjust the parameters as needed to optimize its effectiveness.
Risk management:
a. Always use a stop target to protect your trading capital and manage risk.
b. Don't risk more than a small percentage of your trading capital on a single trade.
c. Be prepared to adjust the strategy or stop trading it if the market conditions change significantly.
Adjusting the Lookback Period and Timeframes for Optimal Strategy Performance
The Range Breaker strategy uses a lookback period to identify swing highs and lows, which serve as the basis for determining entry and exit points for long and short positions. By adjusting the lookback period and analyzing different timeframes, you can potentially find the best strategy configuration for each specific asset.
Adjusting the lookback period:
The lookback period is a critical parameter that affects the sensitivity of the strategy to price movements. A shorter lookback period will make the strategy more sensitive to smaller price fluctuations, resulting in more frequent trading signals. On the other hand, a longer lookback period will make the strategy less sensitive, generating fewer signals but potentially capturing larger price movements.
To optimize the lookback period for a specific asset, you can test different lookback values and compare their performance in terms of risk-adjusted returns, win rate, and other relevant metrics. Keep in mind that using an overly short lookback period may lead to overtrading and increased transaction costs, while an overly long lookback period may cause the strategy to miss profitable trading opportunities.
Analyzing different timeframes:
Timeframes refer to the duration of each bar or candlestick on the chart. Shorter timeframes (e.g., 5-minute, 15-minute, or 30-minute) focus on intraday price movements, while longer timeframes (e.g., daily, weekly, or monthly) capture longer-term trends. The choice of timeframe affects the number of trading signals generated by the strategy and the length of time each position is held.
To find the best strategy for each asset, you can test the Range Breaker strategy on different timeframes and analyze its performance. Keep in mind that shorter timeframes may require more active monitoring and management due to the increased frequency of trading signals. Longer timeframes, on the other hand, may require more patience as positions are held for extended periods.
Finding the best strategy for each asset:
Every asset has unique price characteristics that may affect the performance of a trading strategy. To find the best strategy for each asset, you should:
a. Test various lookback periods and timeframes, observing the strategy's performance in terms of profitability, risk-adjusted returns, and win rate.
b. Consider the asset's historical price behavior, such as its volatility, liquidity, and trend-following or mean-reverting tendencies.
c. Evaluate the strategy's performance during different market conditions, such as bullish, bearish, or sideways markets, to ensure its robustness.
d. Keep in mind that each asset may require a unique set of strategy parameters for optimal performance, and there may be no one-size-fits-all solution.
By experimenting with different lookback periods and timeframes, you can fine-tune the Range Breaker strategy for each specific asset, potentially improving its overall performance and adaptability to changing market conditions. Always practice proper risk management and be prepared to make adjustments as needed.
Remember that trading strategies carry inherent risk, and past performance is not indicative of future results. Always practice proper risk management and consider your own risk tolerance before trading with real money.
Baseline Cross Qualifier Volatility Strategy with HMA Trend BiasFor trading ES on 30min Chart
Trading Rules
Post Baseline Cross Qualifier (PBCQ): If price crosses the baseline but the trade is invalid due to additional qualifiers, then the strategy doesn't enter a trade on that candle. This setting allows you override this disqualification in the following manner: If price crosses XX bars ago and is now qualified by other qualifiers, then the strategy enters a trade.
Volatility: If price crosses the baseline, we check to see how far it has moved in terms of multiples of volatility denoted in price (ATR x multiple). If price has moved by at least "Qualifier multiplier" and less than "Range Multiplier", then the strategy enters a trade. This range is shown on the chart with yellow area that tracks price above/blow the baseline. Also, see the dots at the top of the chart. If the dots are green, then price passes the volatility test for a long. If the dots are red, then price passes the volatility test for a short.
Take Profit/Stoploss Quantity Removed
1 Take Profit: 100% of the trade is closed when the profit target or stoploss is reached.
2 Take Profits: Quantity is split 50/50 between Take Profit 1 and Take Profit 2
3 Take Profits: Quantify is split 50/25/25.
Stratgey Inputs
Baseline Length
37
Post Baseline Cross Qualifier Enabled
On
Post Baseline Cross Qualifier Bars Ago
9
ATR Length
9
Volatility Multiplier
0
Volatility Range Multiplier
10
Volatility Qualifier Multiplier
2
Take Profit Type
1 Take Profit
HMA Length
11
