Mystic Pulse V2.0 Optimized Long [CHE]credits to youtuber : youtu.be
Key Insights
Strategy outperforms buy & hold BTC by 245%
Only 1 losing year (2022 bear market: -18.45%)
Average win (+19.24%) is 4.2× larger than average loss (-4.57%)
No repainting - all signals confirmed at bar close
The strategy file is ready to copy into TradingView. Apply it to BTCUSD 1D with the settings specified (100% equity, 0.1% commission, 1 tick slippag
Forecasting
sullaojo 3mHere is the English translation for the alert setup instructions:
**How to Set Up Alerts (After Adding the Code)**
1. Click the **Add to chart** button to apply the indicator to your graph.
2. Click the **Alarm Clock icon (Alerts)** on the top right toolbar of TradingView, or press `Alt + A`.
3. In the **Condition** field:
* Select the indicator named **"MA Crossover Buy Alert..."**
* Select **"แจ้งเตือนซื้อ (Buy Alert)"** to receive only buy signals.
4. In the **Trigger** (or Options) section: Select **Once per bar close**.
*(This is recommended per the textbook to confirm that the closing price actually crossed the line, avoiding false signals during intraday volatility.)*
5. Check **Notify on App** (for mobile) or **Show pop-up** as desired, then click **Create**.
Now, when the moving averages cross according to the textbook's conditions, the system will send you an alert immediately!
EMA 1 & SALMA Intersection StrategyTrading Strategy: EMA 1 & SALMA Crossover System
This strategy is a Trend-Following system that focuses on the direct interaction between the price (represented by EMA 1) and a smoothed trendline (SALMA). Instead of relying on the color changes of the indicator, it uses mechanical crossover signals to enter and exit trades.
1. Indicators Used
EMA 1 (Exponential Moving Average): Since the period is 1, it effectively represents the Current Price. It reacts instantly to every market move.
SALMA v3.0 (Smoothed Adaptive Lattice Moving Average): A double-smoothed moving average that acts as the "Base Line" or "Trend Support/Resistance."
RSI (Relative Strength Index): Used as a Momentum Filter to ensure we don't trade against the market's strength.
2. Buy (Long) Entry Rules
You enter a Long position when the following conditions are met:
The Crossover: The EMA 1 (Price) crosses ABOVE the SALMA line. This indicates that the short-term momentum is shifting higher than the average trend.
The Filter (RSI): The RSI must be above 50. This confirms that the buyers are in control and the upward move has enough strength.
3. Sell (Short) Entry Rules
You enter a Short position when the following conditions are met:
The Crossunder: The EMA 1 (Price) crosses BELOW the SALMA line. This indicates a breakdown in price action.
The Filter (RSI): The RSI must be below 50. This confirms that the sellers are dominating and the downward momentum is real.
4. Key Advantages of This System
Objectivity: You don't guess based on the color of the line; you wait for a clear physical break (cross) of the line.
Precision: By using EMA 1, you get the earliest possible entry signal compared to slower moving averages.
False Signal Protection: The RSI 50 filter prevents you from entering "weak" trades where the price crosses the line but lacks the volume or momentum to continue.
Conditional-range High/Low adoptive-MA Crossover StrategyDeveloped from the doctoral research of Abu-Kadunagra at ****** University on topic of Digital Finance and Crypto in Australia, this strategy implements a "Campaign-Based Adaptive Execution" framework. It moves beyond simple entries and exits by treating each market engagement as a multi-phase campaign with distinct operational states. The system intelligently identifies cyclical turning points, then employs a feedback-driven approach to capital allocation—reinforcing successful momentum with pyramiding while deploying controlled defensive averaging during temporary setbacks. By anchoring its exit mechanism to dynamically updated market structure rather than static profit targets, the algorithm seeks to capture cyclical momentum while maintaining disciplined risk parameters. This research-driven approach represents an evolution toward state-aware algorithmic systems that adapt their tactics in real-time based on market phase recognition.
ParetoCapital AlogrithmThis strategy is a volatility-based breakout system designed to trade only when the market shows sufficient expansion and directional clarity.
It operates by:
Filtering market regime using a long-term trend reference to avoid trading against dominant momentum.
Activating only during elevated volatility, ensuring trades are taken when price movement has enough energy to justify risk.
Entering via breakout orders, not market orders, so trades are triggered only if price confirms continuation.
Applying strict risk control, with capital usage and risk capped per trade.
Separating backtest logic from live execution, using fixed external order sizing for consistency in automation.
The strategy is intended for systematic, automated execution and avoids overtrading by remaining inactive during low-volatility or unclear market conditions.
mucip sat stratejisiThis strategy performs scaled short entries across multiple timeframes.
Position additions are executed using small capital allocations (1–2% per entry) to manage risk efficiently.
It is primarily optimized for major cryptocurrencies.
The strategy is designed for futures markets and operates with leverage in the 10–15x range.
CPG - Institutional Premium Arbitrage SystemConcept & Logic:
This strategy captures institutional sentiment by analyzing the Cross-Exchange Arbitrage Data between Coinbase (USD pair) and Binance (USDT pair). Instead of using raw price difference which is noisy, this script employs a Proprietary Dynamic Threshold Algorithm. It normalizes the premium data using a custom volatility-adjusted window to filter out retail noise and identify genuine "Whale Accumulation" zones.
Key Features:
Data Source: Real-time BTC/USD vs BTC/USDT spread analysis.
Signal Filtering: The proprietary algorithm (closed-source logic) dynamically adjusts upper and lower bands to prevent false signals during low liquidity periods.
Execution:
Bullish: When the premium breaks the dynamic upper threshold (Strong Institutional Buying).
Bearish: When the premium drops below the dynamic lower threshold (Institutional Selling).
Usage:
Note: The dynamic threshold algorithm is specifically calibrated for Bitcoin's unique liquidity structure. Extensive backtesting shows that this logic is NOT suitable for altcoins (like ETH or SOL). Please strictly use it on BTC pairs.
策略核心:
本策略透過分析 Coinbase (USD) 與 Binance (USDT) 之間的跨交易所資金流 (Arbitrage Data),來捕捉機構投資者的動向。 原始的價差數據通常充滿雜訊,因此本腳本內建了一套**「獨家動態閥值演算法」**。該算法能對數據進行平滑處理與正規化,有效過濾市場雜訊,精準識別出機構大戶的資金流向。
功能特點:
數據源: 即時運算 BTC/USD 與 BTC/USDT 的溢價差。
獨家過濾: 閉源的動態演算法會根據波動率自動調整上下軌閥值,避免假突破。
交易訊號:
看多: 溢價突破動態上軌(機構強力買入)。
看空: 溢價跌破動態下軌(機構拋售)。
用法:
注意: 本策略的動態閥值演算法是針對比特幣的流動性結構進行嚴格校準的。回測數據顯示,此邏輯不適用於 ETH 或 SOL 等其他幣種。請務必僅在 BTC 圖表上使用。
Supertrend Strategy PRO FiltersSupertrend Strategy — PRO Filters is an extended trend-following strategy based on the classic SuperTrend indicator, enhanced with 7 independent professional entry-quality filters, a Stop Loss / Take Profit system, and higher timeframe support.
The strategy is designed for intraday and swing trading on liquid instruments (stocks, futures, cryptocurrencies).
The core logic of the strategy
The strategy is built around the SuperTrend indicator calculated using ATR:
Long — when the trend changes from bearish to bullish
Short — when the trend changes from bullish to bearish
The trend reversal is determined by a breakout of the dynamic SuperTrend lines (up / down), which adapt to market volatility.
Filter system (7 levels)
Each filter can be enabled or disabled independently, allowing the strategy to be adapted to any market and trading style.
ATR Regime Filter
Purpose: trading only during active market phases
An entry is allowed when the current ATR is above its average value
Filters out flat and low-volatility periods
Higher Timeframe Trend Filter
Purpose: trading only in the direction of the higher timeframe trend
Uses SuperTrend on the higher timeframe
Long — only when the HTF trend is bullish
Short — only when the HTF trend is bearish
RSI Impulse Filter
Purpose: filtering out weak and late impulses
Long: RSI above a specified level
Short: RSI below a specified level
Candle Quality Filter
Purpose: excluding entries on “noisy” candles
Entries are allowed only when the candle body is significantly larger than the wicks
Helps avoid false breakouts
SuperTrend Slope Filter
Purpose: confirming trend strength
The slope of the SuperTrend lines is analyzed
Entries are allowed only when sufficient momentum is present
Volume Filter
Purpose: confirming price movement with volume
Volume must exceed the SMA of volume by a multiplier
Filters out moves without participation from large players
EMA Trend Filter
Purpose: additional direction filter
Long — price above EMA
Short — price below EMA
Final entry conditions
A trade is opened only when all of the following are met:
A SuperTrend trend-change signal
All enabled filters
This significantly reduces the number of trades while improving their quality.
Risk management (SL / TP)
An optional fixed-risk system:
Take Profit — as a percentage of the entry price
Stop Loss — as a percentage of the entry price
Works identically for both Long and Short positions
Usage recommendations
Best results are typically achieved on 15m–1h timeframes
It is recommended to optimize filters for each specific instrument
Especially effective in markets with strong, well-defined trends
Disclaimer
This strategy is intended for analysis and educational purposes only.
Before using it in live trading, be sure to conduct your own testing and optimization.
Supertrend Strategy — PRO Filters — это расширенная трендовая стратегия на базе классического SuperTrend, дополненная 7 независимыми профессиональными фильтрами качества входа, системой Stop Loss / Take Profit и поддержкой старшего таймфрейма.
Стратегия предназначена для интрадей- и свинг-торговли на ликвидных инструментах (акции, фьючерсы, криптовалюты).
Базовая логика стратегии
В основе стратегии лежит индикатор SuperTrend, построенный на ATR:
Long — при смене тренда с нисходящего на восходящий
Short — при смене тренда с восходящего на нисходящий
Смена направления определяется пробоем динамических линий SuperTrend (up / down), адаптирующихся к волатильности рынка.
Система фильтров (7 уровней)
Каждый фильтр можно включать или отключать независимо, что позволяет адаптировать стратегию под любой рынок и стиль торговли.
ATR Regime Filter
Назначение: торговля только в активной фазе рынка
Вход разрешён, если текущий ATR выше своего среднего значения
Отсекает флэт и низковолатильные периоды
Higher Timeframe Trend Filter
Назначение: торговля только в сторону тренда старшего таймфрейма
Используется SuperTrend на HTF
Long — только при восходящем тренде HTF
Short — только при нисходящем
RSI Impulse Filter
Назначение: фильтрация слабых и запаздывающих импульсов
Long: RSI выше заданного уровня
Short: RSI ниже заданного уровня
Candle Quality Filter
Назначение: исключение входов по «шумным» свечам
Вход только если тело свечи существенно больше фитилей
Помогает избежать ложных пробоев
SuperTrend Slope Filter
Назначение: подтверждение силы тренда
Анализируется наклон линий SuperTrend
Вход разрешён только при достаточной динамике
Volume Filter
Назначение: подтверждение движения объёмом
Объём должен превышать SMA объёма с коэффициентом
Исключает входы без участия крупных игроков
EMA Trend Filter
Назначение: дополнительный фильтр направления
Long — цена выше EMA
Short — цена ниже EMA
Итоговые условия входа
Сделка открывается только при одновременном выполнении:
Сигнала смены тренда SuperTrend
Всех активированных фильтров
Это значительно снижает количество сделок, но повышает их качество.
Управление рисками (SL / TP)
Опциональная система фиксированного риска:
Take Profit — в процентах от цены входа
Stop Loss — в процентах от цены входа
Работает одинаково для Long и Short
Рекомендации по использованию
Лучшие результаты показывает на 15m–1h таймфреймах
Рекомендуется оптимизация фильтров под конкретный инструмент
Особенно эффективна на рынках с выраженными трендами
Дисклеймер
Стратегия предназначена для анализа и обучения.
Перед использованием в реальной торговле обязательно проведите собственное тестирование и оптимизацию.
Переведи на английский. Не форматироу просто перевод
SaLaSaLa V6 5m By Aleem MubarakThis strategy uses RSI-MA, Multi-timeframe crossing of RSI, Multi-timeframe crossing of MA and the Crossing of RSI with MA itself on the baseline timeframe (5 minutes), while the alignment timeframes are 15m, 1hr, 4hr.
It uses Bolinger Bands to filter out false breakouts and uses an adjustable step-wise trailing as the exit conditions, so for this reason the strategy has a trailing take profit.
This strategy works best on 5 minutes timeframe for scalpers.
You may find the backtesting result using the tester option on trading view.
Just Integrate your broker on Trading View and make the strategy pick trades automatically and watch your investment grow.
Credit to
Lux Algo, Techno Bloom for their indicators which was used as vision during checks
Momentum Quality Index Strategyfiles.fm
Welcome to the Momentum Quality Index Strategy!
This is a fairly conservative strategy with a sharp criteria for entries and taking profits. This strategy has been tested amongst the top 50 stocks with volatility over 2%, and the verdict was that the profitability was often times over 85% profitability, often times reaching over 90% profitability. This strategy thrives in more volatile environments, often times beating the buying and holding strategy YTD performance by large margins.
This strategy is highly optimized for the 30 minute chart, giving insights into shorter term movements. It is based on cash trades of $1,000 per position, with a maximum of 4 trades being placed at once.
This strategy is optimized for common stock trading in more liquid markets, and not yet optimized for options trading (however I plan on developing highly profitable strategies for this purpose soon). The take profit is customizable.
I would refer to the image link I have posted at the top of this article for the strategy's effectiveness. The strategy report on this article isn't accurate, as this strategy is based on trading $1,000 per trade, therefore over longer term periods of time will not be as successful due to the fact that there is no compounding. However, over the course of smaller time frames (such as one year), it beats buying and holding of many assets.
This strategy is meant for day trading and short term swing trading, and is not meant to beat buying and holding of successful assets over the course of long periods of time.
ORB Strategy - EnhancedThis algo is for setting and forgetting ORB. Does require an understanding of how to tweak trading factors
NIFTY T1 & T2 Strategy (65% SL, 15:15 Exit)Time based trading strategy without any indicator and reflecting operators move
ARVEXV1“Failed Reversal – Opposite Candle Only (No Doji/Hammer/Hanging Man)”:
This strategy captures failed reversal attempts where the current candle is opposite to the previous candle and volume is higher. It enters long if a bearish candle fails to break a previous bullish candle’s low, and short if a bullish candle fails to break a previous bearish candle’s high. Signals are canceled for Doji, Hammer, or Hanging Man candles. Entries only, fully backtestable.
Velocity SwingtraderThe intended objective of this indicator to gauge trend and momentum and find trades that are at the beginning of a trend change for longer periods of time (days, weeks, months).
12M Return Strategy This strategy is based on the original Dual Momentum concept presented by Gary Antonacci in his book “Dual Momentum Investing.”
It implements the absolute momentum portion of the framework using a 12-month rate of change, combined with a moving-average filter for trend confirmation.
The script automatically adapts the lookback period depending on chart timeframe, ensuring the return calculation always represents approximately one year, whether you are on daily, weekly, or monthly charts.
How the Strategy Works
1. 12-Month Return Calculation
The core signal is the 12-month price return, computed as:
(Current Price ÷ Price from ~1 year ago) − 1
This return:
Plots as a histogram
Turns green when positive
Turns red when negative
The lookback adjusts automatically:
1D chart → 252 bars
1W chart → 52 bars
1M chart → 12 bars
Other timeframes → estimated to approximate 1 calendar year
2. Trend Filter (Moving Average of Return)
To smooth volatility and avoid noise, the strategy applies a moving average to the 12M return:
Default length: 12 periods
Plotted as a white line on the indicator panel
This becomes the benchmark used for crossovers.
3. Trade Signals (Long / Short / Cash)
Trades are generated using a simple crossover mechanism:
Bullish Signal (Go Long)
When:
12M Return crosses ABOVE its MA
Action:
Close short (if any)
Enter long
Bearish Signal (Go Short or Go Flat)
When:
12M Return crosses BELOW its MA
Action:
If shorting is enabled → Enter short
If shorting is disabled → Exit position and go to cash
Shorting can be enabled or disabled with a single input switch.
4. Position Sizing
The strategy uses:
Percent of Equity position sizing
You can specify the percentage of your portfolio to allocate (default 100%).
No leverage is required, but the strategy supports it if your account settings allow.
5. Visual Signals
To improve clarity, the strategy marks signals directly on the indicator panel:
Green Up Arrows: return > MA
Red Down Arrows: return < MA
A status label shows the current mode:
LONG
SHORT
CASH
6. Backtest-Ready
This script is built as a full TradingView strategy, not just an indicator.
This means you can:
Run complete backtests
View performance metrics
Compare long-only vs long/short behavior
Adjust inputs to tune the system
It provides a clean, rule-driven interpretation of the classic absolute momentum approach.
Inspired By: Gary Antonacci – Dual Momentum Investing
This script reflects the absolute momentum side of Antonacci’s original research:
Uses 12-month momentum (the most statistically validated lookback)
Applies a trend-following overlay to control downside risk
Recreates the classic signal structure used in academic studies
It is a simplified, transparent version intended for practical use and educational clarity.
Disclaimer
This script is for educational and research purposes only.
Historical performance does not guarantee future results.
Always use proper risk management.
Cat Cushion Position SizingThis strategy is for people who don’t want to guess position size every time.
It looks at how volatile the market is and then tells you how many units to hold so your risk per trade stays roughly the same – whether the chart is calm or crazy.
What it does
Measures how “shaky” the price is day by day (volatility)
Blends recent volatility with a long-term average so it doesn’t overreact to one weird day
Uses your Risk per Trade (%) setting to calculate how big your position should be
Adds a buffer zone so it doesn’t trade every tiny wiggle and burn commissions
Shows a small performance table on the chart:
• Average annual return (from backtest)
• Sharpe ratio
• Average drawdown per trade
• Current position size as % of equity
How it thinks about risk
When the market is calmer → volatility is lower → position size can be bigger
When the market is wild → volatility is higher → position size becomes smaller
You control the “spiciness” with:
• Risk per Trade (%) – how much of your equity you’re willing to risk on each position
• Change Sensitivity (%) – wider buffer = fewer trades, lower costs; tighter buffer = more frequent rebalancing
Good use cases
Index ETFs (e.g. AMEX:SPY , NASDAQ:ACWI ) or other liquid instruments
People who:
• Already have a direction/idea (bullish on the index long term)
• Want the position sizing to adapt automatically with volatility
• Prefer “set the rules, let it run” rather than staring at the screen
Inputs to pay attention to
Risk per Trade (%)
• Conservative: ~1–2%
• Balanced: ~3–4%
• Aggressive: 5%+ (handle with care)
Important notes
This is a position sizing / risk strategy, not a magical “always win” tool
Works best when combined with:
• A clear idea of what you want to trade (e.g. broad index ETFs)
• A realistic risk profile (don’t just max the risk because the backtest looks better)
Backtest results are not a promise of future returns
Educational use only – this is not financial advice. Please test on your own, tweak to your comfort level, and don’t bet the rent money 😉
If you like systematic, “low-drama” investing (and want to spend more time chilling like a cat 🐱), this script helps the math side stay under control in the background.
BTC Mon 8am Buy / Wed 2pm Sell (NY Time, Daily + Intraday)This strategy implements a fixed weekly time-based trading schedule for Bitcoin, using New York market hours as the reference clock. It is designed to test whether a consistent pattern exists between early-week accumulation and mid-week distribution in BTC price behavior.
Entry Rule — Monday 8:00 AM (NY Time)
The strategy enters a long position every Monday at exactly 08:00 AM Eastern Time, one hour after the U.S. equities market pre-open activity begins influencing global liquidity.
This timing attempts to capture early-week directional moves in Bitcoin, which sometimes occur as traditional markets come online.
Exit Rule — Wednesday 2:00 PM (NY Time)
The strategy closes the position every Wednesday at 2:00 PM Eastern Time, a point in the week where:
U.S. equity markets are still open
BTC often experiences mid-week volatility rotations
Liquidity is generally high
This exit removes exposure before later-week uncertainty and gives a consistent, measurable time window for each trade.
Timeframe Compatibility
Works on intraday charts (recommended 1h or lower) using precise time-based triggers.
Also runs on daily charts, where entries and exits occur on the Monday and Wednesday bars respectively (daily charts cannot show intraday timestamps).
All timestamps are synced to America/New_York regardless of the exchange’s native timezone.
Trading Frequency
Exactly one trade per week, preventing overtrading and allowing comparison of weekly performance across years of historical BTC price data.
Purpose of the Strategy
This is not a value-based or trend-following system, but a behavioral/time-cycle analysis tool.
It helps evaluate whether a repeating short-term edge exists based solely on:
Weekday timing
Liquidity cycles
Institutional market influence
BTC’s habitual early-week momentum patterns
It is ideal for:
Backtesting weekly BTC behavior
Studying time-based edges
Comparing alternative weekday/time combinations
Visualizing weekly P&L structure
Risk Notes
This strategy does not attempt to predict price direction and should not be assumed profitable without robust backtesting.
Time-based edges can appear, disappear, or invert depending on macro conditions.
There is no stop loss or risk management included by default, so the strategy reflects raw timing-based performance.
Empire OS Automated Trading • Institutional-grade executionEmpire OS – 9/40 EMA Dynamic Momentum Strategy
This strategy isn’t just EMAs — it’s a dynamic entry and exit system built around real-time price behavior. The 9/40 EMA setup gives the base trend direction, and the internal engine calculates every entry, stop, and target using recent price action and a 14-ATR volatility model.
Everything adjusts automatically:
• Entries react to momentum shifts based on the 9/40 EMA separation
• Stops tighten or widen based on the current 14-ATR reading
• Targets scale with real market volatility (not fixed numbers)
• Risk-to-Reward is calculated on the fly for cleaner, stronger trades
• Exits are based on structure + volatility, not random lines
Most strategies use fixed stops, fixed R:R, or standard EMA pairs that anyone can copy.
This one adapts to the market in real time — making every trade unique to current conditions.
It’s rare because almost nobody builds a retail strategy that:
Uses a non-standard 9/40 EMA combo
Calculates stops + targets off real volatility
Adjusts risk reward based on live price activity
Filters entries through momentum AND price structure
Keeps drawdown tight while catching high-quality moves
This is the official Empire OS version — built for consistency, momentum accuracy, and prop-firm scalability.
SSL ST Strategy – Accuracy Enhanced v2.0 (Parser Safe)This strategy is built to identify high-probability trend breakouts using a combination of SSL Channel, Baseline, Hull / EMA signals, and Candle-based confirmations.
The goal is to filter noise, avoid false breakouts, and enter only when the trend is truly shifting.
This strategy identifies high-probability trend breakouts using SSL Channel, Baseline, Hull/EMA, and candle
confirmations.
1. SSL shows trend shift when price breaks high/low levels.
2. Baseline filters direction (price above = buy bias, below = sell bias).
3. Hull/EMA gives early momentum confirmation.
4. Candle breakout ensures real momentum (breaks previous high/low).
5. Optional filters: ATR, reversal logic, continuation entries.
6. Exits occur on SSL flip, baseline cross, or weakness
Disclaimer
This strategy is provided strictly for educational and informational purposes only. It does not guarantee any profit, nor does it protect against losses of any kind. Financial markets are inherently unpredictable, and any market movement can only be assumed or estimated with a probability that is never guaranteed and can often be no better than a 50/50 chance.
By using this strategy, you acknowledge that all trading decisions are made solely at your own risk. I am not liable for any profits, losses, or financial consequences incurred by anyone using or relying on this strategy. Always perform your own research, manage your risk responsibly, and consult with a qualified financial advisor before trading.
Liquidity Sweep & FVG StrategyThis strategy combines higher-timeframe liquidity levels, stop-hunt (sweep) logic, Fair Value Gaps (FVGs) and structure-based take-profits into a single execution engine.
It is not a simple mash-up of indicators: every module (HTF levels, sweeps, FVGs, ZigZag, sessions) feeds the same entry/exit logic.
1. Core Idea
The script looks for situations where price:
Sweeps a higher-timeframe high/low (takes liquidity around obvious levels),
Then forms a displacement candle with a gap (FVG) in the opposite direction,
Then uses the edge of that FVG as a limit entry,
And manages exits using unswept structural levels (ZigZag swings or HTF levels) as targets.
The intent is to systematically trade failed breakouts / stop hunts with a defined structure and risk model.
It is a backtesting / study tool, not a signal service.
2. How the Logic Works (Conceptual)
a) Higher-Timeframe Liquidity Engine
Daily, Weekly and Monthly highs/lows are pulled via request.security() and stored as HTF liquidity levels.
Each level is drawn as a line with optional label (1D/1W/1M High/Low).
A level is marked as “swept” once price trades through it; swept levels may be removed or shortened depending on settings.
b) Sweep & Manipulation Filter
A low sweep occurs when the current low trades through a stored HTF low.
A high sweep occurs when the current high trades through a stored HTF high.
If both a high and a low are swept in the same bar, the script flags this as “manipulation” and blocks new entries around that noise.
The script also tracks the sweep wick, bar index and HTF timeframe for later use in SL placement and labels.
c) FVG Detection & Management
FVGs are defined using a 3-candle displacement model:
Bullish FVG: high < low
Bearish FVG: low > high
Only gaps larger than a minimum size (ATR-based if no manual value is set) are kept.
FVGs are stored in arrays as boxes with: top, bottom, mid (CE), direction, and state (filled / reclaimed).
Boxes are auto-extended and visually faded when price is far away, or deleted when filled.
d) Entry Conditions (Sweep + FVG)
For each recent sweep window:
After a low sweep, the script searches for the nearest bullish FVG below price and uses its top edge as a long limit entry.
After a high sweep, it searches for the nearest bearish FVG above price and uses its bottom edge as a short limit entry.
A “knife protection” check blocks trades where price is already trading through the proposed stop.
Only one entry per sweep is allowed; entries are only placed inside the configured NY trading sessions and only if no manipulation flag is active and EOD protection allows it.
e) Stop-Loss Placement (“Tick-Free” SL)
The stop is not placed directly on the HTF level; instead, the script scans a window around the sweep bar to find a local extreme:
Longs: lowest low in a configurable bar window around the sweep.
Shorts: highest high in that window.
This produces a structure-based SL that is generally outside the main sweep wick.
f) Take-Profit Logic (ZigZag + HTF Levels)
A lightweight ZigZag engine tracks swing highs/lows and removes levels that have already been broken.
For intraday timeframes (< 1h), TP candidates come from unswept ZigZag swings above/below the entry.
For higher timeframes (≥ 1h), TP candidates fall back to unswept HTF liquidity levels.
The script picks up to two targets:
TP1: nearest valid target in the trade direction (or a 2R fallback if none exists),
TP2: second target (or a 4R fallback if none exists).
A multi-TP model is used: typically 50% at TP1, remainder managed towards TP2 with breakeven plus offset once TP1 is hit.
g) Session & End-of-Day Filters
Three predefined NY sessions (Early, Open, Afternoon) are available; entries are only allowed inside active sessions.
An End-of-Day filter checks a user-defined NY close time and:
Blocks new entries close to the end of the day,
Optionally forces flat before the close.
3. Inputs Overview (Conceptual)
Liquidity settings: which HTF levels to track (1D/1W/1M), how many to show, and sweep priority (highest TF vs nearest vs any).
FVG settings: visibility radius, search window after a sweep, minimum FVG size.
ZigZag settings: swing length used for TP discovery.
Execution & protection: limit order timeout, breakeven offset, EOD protection.
Visuals: labels, sweep markers, manipulation warning, session highlighting, TP lines, etc.
For exact meaning of each input, please refer to the inline comments in the open-source code.
4. Strategy Properties & Backtesting Notes
Default strategy properties in this script:
Initial capital: 100,000
Order size: 10% of equity (strategy.percent_of_equity)
Commission: 0.01% per trade (adjust as needed for your broker/asset)
Slippage: must be set manually in the Strategy Tester (recommended: at least a few ticks on fast markets).
Even though the order size is 10% of equity, actual risk per trade depends on the SL distance and is typically much lower than 10% of the account. You should still adjust these values to keep risk within what you personally consider sustainable (e.g. somewhere in the 1–2% range per trade).
For more meaningful results:
Test on liquid instruments (e.g. major indices, FX, or liquid futures).
Use enough history to reach 100+ closed trades on your market/timeframe.
Always include realistic commission and slippage.
Do not assume that past performance will continue.
5. How to Use
Apply the strategy to your preferred symbol and timeframe.
Set broker-like commission and slippage in the Strategy Tester.
Adjust:
HTF levels (1D/1W/1M),
Sessions (NY windows),
FVG search window and minimum size,
ZigZag length and EOD filter.
Observe how entries only appear:
After a HTF sweep,
In the configured session,
At a FVG edge,
With TP lines anchored at unswept structure / liquidity.
Use this primarily as a research and backtesting tool to study how your own ICT / SMC ideas behave over a large sample of trades.
6. Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice, and it does not guarantee profitability. Always validate results with realistic assumptions and use your own judgment before trading live.
Simplified WMA Ribbon · Majority Rule StrategyThis strategy is a simplified WMA-ribbon “majority rule” system. It compares five fast WMAs (10–30) with five slow WMAs (70–90) and counts how many bullish or bearish pairs are strongly separated by a small ε-buffer. A long (short) position is opened only when a bullish (bearish) majority is reached and closed when that majority weakens or an opposite majority appears. Position size is calculated from a fixed USD amount and leverage, candles are colored by current position, and a mini dashboard shows the number of bullish/bearish pairs and the current status (LONG / SHORT / FLAT).
GraalSTRATEGY DESCRIPTION — “GRAAL”
GRAAL is an advanced algorithmic crypto-trading strategy designed for trend and semi-trend market conditions. It combines ATR-based trend/flat detection, dynamic Stop-Loss and multi-level Take-Profit, break-even (BE) logic, an optional trailing stop, and a “lock-on-trend” mechanism to hold positions until the market structure truly reverses.
The strategy is optimized for Binance, OKX and Bybit (USDT-M and USDC-M futures), but can also be used on spot as an indicator.
Core Logic
Trend Detection — dynamic trend zones built using ATR and local high/low structure.
Entry Logic — positions are opened only after trend confirmation and a momentum-based local trigger.
Exit Logic:
fixed TP levels (TP1/TP2/TP3),
dynamic ATR-based SL,
break-even move after TP1 or TP2,
optional trailing stop.
Lock-on-Trend — positions remain open until an opposite trend signal appears.
Noise Protection — flat filter disables entries during low-volatility conditions.
Key Advantages
Sophisticated and reliable risk-management system.
Minimal false entries due to robust trend filtering.
Optional trailing logic to maximize profit during strong directional moves.
Works well on BTC, ETH and major altcoins.
Easily adaptable for various timeframes (1m–4h).
Supports full automation via OKX / WunderTrading / 3Commas JSON alerts.
Recommended Use Cases
Crypto futures (USDT-M / USDC-M).
Intraday trading (5m–15m–1h).
Swing trading (4h–1D).
Fully automated signal-bot execution.
Important Notes
This is an algorithmic strategy, not financial advice.
Strategy Tester performance may differ from real execution due to liquidity, slippage and fees.
Always backtest and optimize parameters for your specific market and asset.
Recommended Settings: LONG only, no TP, no SL, Flat Policy: Hold, TP3 Mode: Trend, Trailing Stop 1.2%, Fixed size 100 USD, Leverage 10×, ATR=14, HH/LL=36.






















