💻 RSI Dual-Band Reversal Strategy (Hacker Mode)This 💻 RSI Dual-Band Reversal Strategy (Hacker Mode) is a mean-reversion trading strategy built on the Relative Strength Index (RSI) indicator.
It identifies potential trend reversals when price momentum reaches extreme overbought or oversold levels — then enters trades expecting the price to revert.
⚙️ Strategy Concept
The RSI measures market momentum on a scale of 0–100.
When RSI is too low, it signals an oversold market → potential buy.
When RSI is too high, it signals an overbought market → potential sell.
This strategy sets two reversal zones using dual RSI bands:
Zone RSI Range Meaning Action
Upper Band 80–90 Overbought Prepare to Sell
Lower Band 10–20 Oversold Prepare to Buy
🧩 Code Breakdown
1. Input Parameters
rsiLength = input.int(14)
upperBandHigh = input.float(90.0)
upperBandLow = input.float(80.0)
lowerBandLow = input.float(10.0)
lowerBandHigh = input.float(20.0)
You can adjust:
RSI Length (default 14) → sensitivity of the RSI.
Upper/Lower Bands → control when buy/sell triggers occur.
2. RSI Calculation
rsi = ta.rsi(close, rsiLength)
Calculates the RSI of the closing price over 14 periods.
3. Signal Logic
buySignal = ta.crossover(rsi, lowerBandHigh)
sellSignal = ta.crossunder(rsi, upperBandLow)
Buy Signal: RSI crosses up through 20 → market rebounding from oversold.
Sell Signal: RSI crosses down through 80 → market turning from overbought.
4. Plotting
RSI line (lime green)
Bands:
🔴 80–90 (Sell Zone)
🟢 10–20 (Buy Zone)
Gray midline at 50 for reference.
Triangle markers for signals:
🟢 “BUY” below chart
🔴 “SELL” above chart
5. Trading Logic
if (buySignal)
strategy.entry("Buy", strategy.long)
if (sellSignal)
strategy.entry("Sell", CRYPTO:BTCUSD strategy.short OANDA:XAUUSD )
Opens a long position on a buy signal.
Opens a short position on a sell signal.
No explicit stop loss or take profit — positions reverse when an opposite signal appears.
🧠 How It Works (Step-by-Step Example)
RSI drops below 20 → oversold → buy signal triggers.
RSI rises toward 80 → overbought → sell signal triggers.
Strategy flips position, always staying in the market (either long or short).
📈 Visual Summary
Imagine the RSI line oscillating between 0 and 100:
100 ────────────────────────────────
90 ───── Upper Band High (Sell Limit)
80 ───── Upper Band Low (Sell Trigger)
50 ───── Midline
20 ───── Lower Band High (Buy Trigger)
10 ───── Lower Band Low (Buy Limit)
0 ────────────────────────────────
When RSI moves above 80 → SELL
When RSI moves below 20 → BUY
⚡ Strategy Profile
Category Description
Type Mean Reversion
Entry Rule RSI crosses up 20 → Buy
Exit/Reverse Rule RSI crosses down 80 → Sell
Strengths Simple, effective in sideways/range markets, minimal lag
Weaknesses Weak in strong trends, no stop-loss or take-profit logic
💡 Suggested Improvements
You can enhance this script by adding:
Stop loss & take profit levels (e.g., % or ATR-based).
Trend filter (e.g., trade only in direction of 200 EMA).
RSI smoothing to reduce noise.
Trend Analizi
AMF PG Strategy v2.3AMF PG Strategy v2.3
1. Core Philosophy: Filtered and Volatility-Aware Trend Following
"AMF PG Strategy" is an advanced trend-following system designed to adapt to the dynamic nature of modern markets. The strategy's core philosophy is not just to follow the trend but also to wait for the right conditions to enter the market.
This is not a "black box." It is a rules-based framework that gives the user full control over various market filters. By requiring multiple conditions to be met simultaneously, the strategy aims to filter out low-quality signals and focus only on high-probability trend opportunities.
2. Core Engine: AMF PG Trend Following
At the heart of the strategy is a proprietary, volatility-aware trend-following mechanism called AMF PG (Praetorian Guard). This engine operates as follows:
Dynamic Bands: Creates a dynamic upper and lower band around the price that is constantly recalculated. The width of these bands is not fixed; It dynamically adjusts based on recent market volatility, volume flow, and price expansion. This adaptive structure allows the strategy to adapt to both calm and high-volatility markets.
Entry Signals: A buy signal is triggered when the price rises above the upper band. A sell signal is triggered when the price falls below the lower band. However, these signals are executed only when all the active filters described below give the green light.
Trailing Stop-Loss: When a position is entered, the opposite band automatically acts as a trailing stop-loss level. For example, when a buy position is opened, the lower band follows the price as a stop-loss. This allows for profit retention and trend continuation.
3. Multi-Layered Filter System: Understanding the Market
The power of this strategy comes from its modular filter system, which allows the user to filter market conditions based on their own analysis. Each filter can be enabled or disabled individually in the settings:
Filter 1: Trend Strength (ADX Filter): This filter confirms whether there is a strong trend in the market. It uses the ADX (Average Directional Index) indicator and only allows trades if the ADX value is above a certain threshold. This helps avoid trading in weak or directionless markets. It also confirms the direction of the trend by checking the position of the DMI (+DI and -DI) lines.
Filter 2: Sideways Market (Chop Index Filter): This filter determines whether the market is excessively choppy or directionless. Using the Chop Index, this filter aims to protect against fakeouts by blocking trades when the market is highly indecisive.
Filter 3: Market Structure (Hurst Exponent Filter): This is one of the strategy's most advanced filters. It analyzes the current market behavior using the Hurst Exponent. This mathematical tool attempts to determine whether a market tends to trend (permanent), tends to revert to the mean (anti-permanent), or moves randomly. This filter ensures that signals are generated only when market structure supports trending trades.
4. Risk Management: Maximum Drawdown Protection
This strategy includes a built-in capital protection mechanism. Users can specify the percentage of their capital they will tolerate to decline from its peak. If the strategy's capital reaches this set drawdown limit, the protection feature is activated, closing all open positions and preventing new trades from being opened. This acts as an emergency brake to protect capital against unexpected market conditions.
5. Automation Ready: Customizable Webhook Alerts
The strategy is designed for traders who want to automate their signals. From the Settings menu, you can configure custom alert messages in JSON format, compatible with third-party automation services (via Webhooks).
6. Strategy Backtest Information
Please note that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTCUSD pair with the following settings:
Test Period: January 1, 2016 - October 31, 2025
Default Position Size: 15% of Capital
Pyramiding: Closed
Commission: 0.0008
Slippage: 2 ticks (Please enter the slippage you used in your own tests)
Testing Approach: The published test includes 423 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
Vandan V2Vandan V2 is an automated trend-following strategy for NASDAQ E-mini Futures (NQ1!).
It uses multi-timeframe momentum and volatility filters to identify high-probability entries.
Includes dynamic risk management and trailing logic optimized for intraday trading.
INDIAN INTRADAY BEASTThe Indian Intraday Beast is a precision-built intraday strategy optimized for the 15-minute timeframe.
It captures high-probability momentum shifts and trend reversals using adaptive price-action logic and proprietary confirmation filters.
Designed for traders who demand clarity, speed, and consistency in India’s fast-paced markets.
US/SPY- Financial Regime Index Swing Strategy Credits: concept inspired by EdgeTools Bloomberg Financial Conditions Index (Proxy)
Improvements: eight component basket, inverse volatility weights, winsorization option( statistical technique used to limit the influence of outliers in a dataset by replacing extreme values with less extreme ones, rather than removing them entirely), slope and price gates, exit guards, table and gradients.
Summary in one paragraph
A macro regime swing strategy for index ETFs, futures, FX majors, and large cap equities on daily calculation with optional lower time execution. It acts only when a composite Financial Conditions proxy plus slope and an optional price filter align. Originality comes from an eight component macro basket with inverse volatility weights and winsorized return z scores that produce a portable yardstick.
Scope and intent
Markets: SPY and peers, ES futures, ACWI, liquid FX majors, BTC, large cap equities.
Timeframes: calculation daily by default, trade on any chart.
Default demo: SPY on Daily.
Purpose: convert broad financial conditions into clear swing bias and exits.
Originality and usefulness
Unique fusion: return z scores for eight liquid proxies with inverse volatility weighting and optional winsorization, then slope and price gates.
Failure mode addressed: false starts in chop and early shorts during easy liquidity.
Testability: all knobs are inputs and the table shows components and weights.
Portable yardstick: z scores center at zero so thresholds transfer across symbols.
Method overview in plain language
Base measures
Return basis: natural log return over a configurable window, standardized to a z score. Winsorization optional to cap extremes.
Components
EQ US and EQ GLB measure equity tone.
CREDIT uses LQD over HYG. Higher credit quality outperformance is risk off so sign is flipped after z score.
RATES2Y uses two year yield, sign flipped.
SLOPE uses ten minus two year yield spread.
USD uses DXY, sign flipped.
VOL uses VIX, sign flipped.
LIQ uses BIL over SPY, sign flipped.
Each component is smoothed by the composite EMA.
Fusion rule
Weighted sum where weights are equal or inverse volatility with exponent gamma, normalized to percent so they sum to one.
Signal rule
Long when composite crosses up the long threshold and its slope is positive and price is above the SMA filter, or when composite is above the configured always long floor.
Short when composite crosses down the short threshold and its slope is negative and price is below the SMA filter.
Long exit on cross down of the long exit line or on a fresh short signal.
Short exit on cross up of the short exit line or on a fresh long signal, or when composite falls below the force short exit guard.
What you will see on the chart
Markers on suggestion bars: L for long, S for short, LX and SX for exits.
Reference lines at zero and soft regime bands at plus one and minus one.
Optional background gradient by regime intensity.
Compact table with component z, weight percent, and composite readout.
Table fields and quick reading guide
Component: EQ US, EQ GLB, CREDIT, RATES2Y, SLOPE, USD, VOL, LIQ.
Z: current standardized value, green for positive risk tone where applicable.
Weight: contribution percent after normalization.
Composite: current index value.
Reading tip: a broadly green Z column with slope positive often precedes better long context.
Inputs with guidance
Setup
Calc timeframe: default Daily. Leave blank to inherit chart.
Lookback: 50 to 1500. Larger length stabilizes regimes and delays turns.
EMA smoothing: 1 to 200. Higher smooths noise and delays signals.
Normalization
Winsorize z at ±3: caps extremes to reduce one off shocks.
Return window for equities: 5 to 260. Shorter reacts faster.
Weighting
Weight lookback: 20 to 520.
Weight mode: Equal or InvVol.
InvVol exponent gamma: 0.1 to 3. Higher compresses noisy components more.
Signals
Trade side: Long Short or Both.
Entry threshold long and short: portable z thresholds.
Exit line long and short: soft exits that give back less.
Slope lookback bars: 1 to 20.
Always long floor bfci ≥ X: macro easy mode keep long.
Force short exit when bfci < Y: macro stress guard.
Confirm
Use price trend filter and Price SMA length.
View
Glow line and Show component table.
Symbols
SPY ACWI HYG LQD VIX DXY US02Y US10Y BIL are defaults and can be changed.
Realism and responsible publication
No performance claims. Past is not future.
Shapes can move intrabar and settle on close.
Execution is on standard candles only.
Honest limitations and failure modes
Major economic releases and illiquid sessions can break assumptions.
Very quiet regimes reduce contrast. Use longer windows or higher thresholds.
Component proxies are ETFs and indexes and cannot match a proprietary FCI exactly.
Strategy notice
Orders are simulated on standard candles. All security calls use lookahead off. Nonstandard chart types are not supported for strategies.
Entries and exits
Long rule: bfci cross above long threshold with positive slope and optional price filter OR bfci above the always long floor.
Short rule: bfci cross below short threshold with negative slope and optional price filter.
Exit rules: long exit on bfci cross below long exit or on a short signal. Short exit on bfci cross above short exit or on a long signal or on force close guard.
Position sizing
Percent of equity by default. Keep target risk per trade low. One percent is a sensible starting point. For this example we used 3% of the total capital
Commisions
We used a 0.05% comission and 5 tick slippage
Legal
Education and research only. Not investment advice. Test in simulation first. Use realistic costs.
MSB Gold Trend Breakout [TV]: The High-Stability Gold Scalper🏆 MSB Gold Trend Breakout : The High-Stability Gold Scalper
This is the official signal for the MSB Pro brand, designed for traders who demand low-drawdown, consistent performance on the XAUUSD (Gold) market.
📈 Verified Performance & Risk Contro l
The strategy's stability has been verified over 1.8 years of historical data.
Max Drawdown (DD): 12.53% (Exceptional capital safety.)
Total Net Profit (1.8 Yrs): +8.15% (Consistent Growth.)
Profit Factor: 1.055 (Proven reliability.)
🛡️ Why Choose This Signal?
True Risk Control: The low drawdown is achieved through a strict EMA filtering system, preventing entry into high-volatility, directionless markets.
Breakout Logic: Uses high-probability breakout movements confirmed by trend alignment (EMA Cross and Trend Filter).
No Martingale/Grid: This is a safe, single-order strategy.
👑 Upgrade to Full License
This signal is priced low to allow you to validate the performance.
Upgrade to the full license ($499) to get:
Lifetime Updates & Future Strategy: Guaranteed access to all future professional upgrades of the MSB Pro Dynamic Risk strategy (V2.0, V3.0, etc.) at no extra cost.
Significant Savings: Purchasing the full license is significantly cheaper than continuous renting.
MoneyPlant-Auto Support Resistance V2.0
🧭 Overview
MoneyPlant – Auto Support Resistance is a professional-grade indicator designed to automatically detect dynamic Support and Resistance levels using real-time market structure.
It combines trend confirmation, structure analysis, and momentum logic to identify high-probability trading zones in all market conditions.
⚙️ Core Concept
This indicator uses a unique combination of classic and proprietary logic to filter only the most relevant S/R levels:
• Dynamic Support/Resistance Mapping: Detects strong reaction levels based on price structure, candle rejection points, and breakout validation.
• EMA & WMA Trend Filter: Uses a triple-moving-average model (default EMA 18, EMA 25, and WMA 7) to confirm current market bias.
• MACD Momentum Filter: Confirms trend strength and helps avoid false breakouts.
• Smart Alignment Logic: Generates signals only when structure, trend, and momentum all align in the same direction.
🧠 How It Works
1. Buy Setup:
When price breaks above a resistance level with bullish EMA/WMA alignment and positive MACD momentum → Buy Signal triggers.
2. Sell Setup:
When price breaks below a support level with bearish EMA/WMA alignment and negative MACD momentum → Sell Signal triggers.
3. Auto-Refreshing Zones:
Support and Resistance zones update dynamically as market structure evolves.
🎯 Best Use Cases
• Works effectively on Stocks, Indices, Forex, and Commodities (e.g., XAUUSD, NIFTY, BANKNIFTY ).
• Ideal for Intraday & Swing Trading (15 min – 1 hour timeframes).
• Fully compatible with TradingView alerts and automation tools.
💡 Key Features
✅ Automatic Support/Resistance detection
✅ Adaptive EMA + WMA + MACD trend logic
✅ Real-time Buy/Sell alerts
✅ Multi-timeframe compatibility
✅ Optimized for clean chart visuals
⚖️ Recommended Settings
• EMA Fast: 18
• EMA Slow: 25
• WMA Filter: 7
• MACD: Default parameters
(Users may adjust EMA/WMA settings according to their own trading style.)
🔒 How to Get Access
To get access to this invite-only script, please send me a private message on TradingView or use the link in my profile.
Once your username is added via Manage Access, you’ll be able to use the indicator.
🧾 Notes for Traders
This tool does not repaint, and it’s meant for educational and analytical purposes only.
Each license is valid for one TradingView username — no resale or redistribution is permitted.
Developed by MoneyPlant
Smart Automation for Professional Traders
AMF PG Consensus Engine v3.5AMF PG Consensus Engine v3.5
1. Core Philosophy: A Multi-Stage Confirmation System for High-Probability Signals
In the world of automated trading, the real challenge isn't generating signals, but filtering out the noise. The AMF PG Consensus Engine is designed to address this challenge. It operates on a simple yet powerful philosophy: a buy or sell signal is valid only if it receives confirmation from multiple, independent analysis modules.
This strategy isn't a "black box." It's a transparent, rules-based framework that transforms market momentum and momentum into a final consensus and then directs a core trend-following engine. The goal is to avoid trading in adverse market conditions and only act when the different analysis layers agree.
2. How the Consensus Engine Works: Two Confirmation Layers
Before the core engine is allowed to seek a trade, the market must go through a two-stage "confirmation" process. Both filters can be enabled or disabled from the settings, allowing users to customize the strategy's stringency level.
Confirmation Module 1: Renko Regime Filter
This module's purpose is to answer a critical question: "Is the market currently in a stable, directional trend, or is it volatile and unstable?" Instead of standard indicators, it creates a timeless Renko chart in the background. A trend is confirmed only if a minimum number of consecutive Renko bricks form in the same direction. This method is extremely effective at filtering out noisy, sideways price movements, which are often unsuccessful for trend-following systems. The brick size can be set to a fixed value or automatically calculated based on the Average True Range (ATR) for better fit.
Confirmation Module 2: Candle Scoring Engine
This module analyzes the raw strength of price action by scoring each candle individually. It evaluates the candle's direction, body size relative to the previous candle, and the change in closing price. These factors are converted into a score for each bar. A cumulative score is then calculated over a user-defined period. A buy trade is only confirmed if this cumulative momentum score exceeds a positive threshold, indicating sustained buying pressure. Conversely, a sell trade requires the score to fall below a negative threshold, indicating sustained selling pressure.
3. Core Engine: AMF PG Trend Follower
When both confirmation modules give the "green light" for a specific direction (e.g., buy), the core AMF PG (Praetorian Guard) engine is activated. This is a proprietary, volatility-sensitive trend-following mechanism.
It calculates a dynamic upper and lower band around the price. These bands are not static; their distance from the price is constantly adjusted based on recent market volatility and price expansion. A trade is initiated when the price breaks out of these bands in the direction confirmed by the consensus engine. The opposing band then serves as the initial trailing stop-loss, adjusted as the trend progresses.
4. Embedded Filters for Additional Security
To further enhance signal quality, the core engine has several embedded filters that are always active and cannot be disabled by the user:
Trend Strength Filter: To confirm that a trend has sufficient strength, a trade will not be initiated unless the ADX (Average Directional Index) is above a certain threshold.
Sideways Market Filter: The Chop Index is used to prevent trading in extremely sideways and directionless markets.
5. Risk Management: Maximum Drawdown Protection
A key feature of this strategy is its built-in capital protection mechanism. Users can set a maximum capital drawdown limit of a percentage. If the strategy's capital falls by this percentage from its peak, the "DD Protect" feature is activated, closing all open positions and preventing new trades from being opened. This acts as a final emergency brake to protect capital during unpredictable market conditions or underperformance of the strategy.
6. Automation-Ready: Customizable Webhook Alerts
This strategy was developed for modern investors looking to automate their trading. Instead of generic alert messages, you can define your own custom alert text directly from the script's settings.
This feature is particularly powerful for connecting to third-party automation services via Webhooks. You can configure the alert message in the JSON format required by your service (such as {"action": "buy", "symbol": "{{ticker}}"}). This allows you to seamlessly connect your strategy signals directly to your trading account.
7. Strategy Backtest Information
Please remember that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTC/USD pair with the following settings:
Test Period: January 1, 2016 - October 31, 2025
Default Position Size: 15% of Capital
Pyramiding: Closed
Commission: 0.0008
Slippage: 2 ticks (Please enter the slippage you used in your own tests)
Testing Approach: The published test includes 799 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
Aurora Vigor 2.2 — Night Vision Edition🧠 Aurora Vigor 2.2 — Night Vision Edition ⚡
Aurora Vigor is a precision-engineered intra-day trading strategy built for futures and prop-firm evaluations.
It blends adaptive moving averages, volatility-adjusted risk control, and session-based logic to capture structured micro-trend moves with disciplined execution.
⚙️ Core Concepts
Dual adaptive moving-average framework (KAMA + EMA) identifies short-term trend alignment.
ATR-based dynamic stop and position sizing maintain consistent risk per trade.
Smart breakeven and progressive trailing secure profit automatically.
Session lock (8 AM–4 PM ET) filters out low-liquidity periods.
Daily profit/loss guardrails stop new entries beyond preset limits.
📊 Recommended Settings
Timeframe : 1 – 5 minutes
Markets : NQ | ES | MNQ | MES | MGC | MCL
Risk per trade : $10 (default)
ATR Multiplier : 0.5
Take Profit : 12 ticks
🌫️ Visual Design
The Aurora Cloud dynamically shifts brightness with volatility—subtle in chop, vivid in momentum—creating a professional, low-glare “night-vision” chart aesthetic.
⚠️ Disclaimer
For educational and research purposes only.
No guarantee of profit or future performance. Always test thoroughly before live use.
Author’s Note: Built for disciplined traders who value structure, consistency, and precision in execution.
ORBSMMAATRVOLREENTRY2Contracts📈 Opening Range Fibonacci Breakout (TradingView Strategy)
Overview:
The Opening Range Fibonacci Breakout strategy is designed to capture high-probability intraday moves by combining the power of the 15-minute opening range, trend confirmation via SMMA, and volume-based momentum filtering.
At the start of each trading session, the script automatically plots the Opening Range Box based on the first 15 minutes of price action — highlighting key intraday support and resistance levels.
How It Works:
Opening Range Setup
The first 15 minutes of the session define the range high and low.
A visual box marks this zone on the chart for easy reference.
Signal Generation
A Smoothed Moving Average (SMMA) with a user-defined period determines overall trend bias.
Candle volume is analyzed to confirm momentum strength.
Long Signal: Price breaks above the opening range high, SMMA trending up, and volume supports the move.
Short Signal: Price breaks below the opening range low, SMMA trending down, and volume supports the move.
Take Profit & Targets
Fibonacci extension levels are automatically plotted from the opening range.
These dynamic levels serve as structured Take Profit (TP) zones for partial or full exits.
Features:
✅ 15-Minute Opening Range Box
✅ Adjustable SMMA period
✅ Volume-based confirmation filter
✅ Automatic Fibonacci profit targets
✅ Visual Long/Short alerts & signals
Ideal For:
Scalpers and intraday traders who rely on early-session momentum, breakout confirmation, and precision exit targets.
Backtested for MNQ/NQ futures trading
SigmaKernel - AdaptiveSigmaKernel - Adaptive Self-Optimizing Multi-Factor Trading System
SigmaKernel - Adaptive is a self-learning algorithmic trading strategy that combines four distinct analytical dimensions—momentum, market structure, volume flow, and reversal patterns—within a machine-learning-inspired framework that continuously adjusts its own parameters based on realized trading performance. Unlike traditional fixed-parameter strategies that maintain static weightings regardless of market conditions or results, this system implements a feedback loop that tracks which signal types, directional biases, and market conditions produce profitable outcomes, then mathematically adjusts component weightings, minimum score thresholds, position sizing multipliers, and trade spacing requirements to optimize future performance.
The strategy is designed for futures traders operating on prop firm accounts or live capital, incorporating realistic execution mechanics including configurable entry modes (stop breakout orders, limit pullback entries, or market-on-open), commission structures calibrated to retail futures contracts ($0.62 per contract default), one-tick slippage modeling, and professional risk controls including trailing drawdown guards, daily loss limits, and weekly profit targets. The system features universal futures compatibility—it automatically detects and adapts to any futures contract by reading the instrument's tick size and point value directly from the chart, eliminating the need for manual configuration across different markets.
What Makes This Approach Different
Adaptive Weight Optimization System
The core differentiation is the adaptive learning architecture. The strategy maintains four independent scoring components: momentum analysis (using RSI multi-timeframe, MACD histogram, and DMI/ADX), market structure detection (breakout identification via pivot-based support/resistance and moving average positioning), volume flow analysis (Volume Price Trend indicator with standard deviation confirmation), and reversal pattern recognition (oversold/overbought conditions combined with structural levels).
Each component generates a directional score that is multiplied by its current weight. After every closed trade, the system performs a retrospective analysis on the last N trades (configurable Learning Period, default 15 trades) to calculate win rates for each signal type independently. For example, if momentum-driven trades won 65% of the time while reversal trades won only 35%, the adaptive algorithm increases the momentum weight and decreases the reversal weight proportionally. The adjustment formula is:
New_Weight = Current_Weight + (Component_Win_Rate - Average_Win_Rate) × Adaptation_Speed
This creates a self-correcting mechanism where successful signal generators receive more influence in future composite scores, while underperforming components are de-emphasized. The system separately tracks long versus short win rates and applies directional bias corrections—if shorts consistently outperform longs, the strategy applies a 10% reduction to bullish signals to prevent fighting the prevailing market character.
Dynamic Parameter Adjustment
Beyond component weightings, three critical strategy parameters self-adjust based on performance:
Minimum Signal Score: The threshold required to trigger a trade. If overall win rate falls below 45%, the system increments this threshold by 0.10 per adjustment cycle, making the strategy more selective. If win rate exceeds 60%, the threshold decreases to allow more opportunities. This prevents the strategy from overtrading during unfavorable conditions and capitalizes on high-probability environments.
Risk Multiplier: Controls position sizing aggression. When drawdown exceeds 5%, risk per trade reduces by 10% per cycle. When drawdown falls below 2%, risk increases by 5% per cycle. This implements the professional risk management principle of "bet small when losing, bet bigger when winning" algorithmically.
Bars Between Trades: Spacing filter to prevent overtrading. Base value (default 9 bars) multiplies by drawdown factor and losing streak factor. During drawdown or consecutive losses, spacing expands up to 2x to allow market conditions to change before re-entering.
All adaptation operates during live forward-testing or real trading—there is no in-sample optimization applied to historical data. The system learns solely from its own realized trades.
Universal Futures Compatibility
The strategy implements universal futures instrument detection that automatically adapts to any futures contract without requiring manual configuration. Instead of hardcoding specific contract specifications, the system reads three critical values directly from TradingView's symbol information:
Tick Size Detection: Uses `syminfo.mintick` to obtain the minimum price increment for the current instrument. This value varies widely across markets—ES trades in 0.25 ticks, crude oil (CL) in 0.01 ticks, gold (GC) in 0.10 ticks, and treasury futures (ZB) in increments of 1/32nds. The strategy adapts all entry buffer calculations and stop placement logic to the detected tick size.
Point Value Detection: Uses `syminfo.pointvalue` to determine the dollar value per full point of price movement. For ES, one point equals $50; for crude oil, one point equals $1,000; for gold, one point equals $100. This automatic detection ensures accurate P&L calculations and risk-per-contract measurements across all instruments.
Tick Value Calculation: Combines tick size and point value to compute dollar value per tick: Tick_Value = Tick_Size × Point_Value. This derived value drives all position sizing calculations, ensuring the risk management system correctly accounts for each instrument's economic characteristics.
This universal approach means the strategy functions identically on emini indices (ES, MES, NQ, MNQ), micro indices, energy contracts (CL, NG, RB), metals (GC, SI, HG), agricultural futures (ZC, ZS, ZW), treasury futures (ZB, ZN, ZF), currency futures (6E, 6J, 6B), and any other futures contract available on TradingView. No parameter adjustments or instrument-specific branches exist in the code—the adaptation happens automatically through symbol information queries.
Stop-Out Rate Monitoring System
The strategy includes an intelligent stop-out rate tracking system that monitors the percentage of your last 20 trades (or available trades if fewer than 20) that were stopped out. This metric appears in the dashboard's Performance section with color-coded guidance:
Green (<30% stop-out rate): Very few trades are being stopped out. This suggests either your stops are too loose (giving back profits on reversals) or you're in an exceptional trending market. Consider tightening your Stop Loss ATR multiplier to lock in profits more efficiently.
Orange (30-65% stop-out rate): Healthy range. Your stop placement is appropriately sized for current market conditions and the strategy's risk-reward profile. No adjustment needed.
Red (>65% stop-out rate): Too many trades are being stopped out prematurely. Your stops are likely too tight for the current volatility regime. Consider widening your Stop Loss ATR multiplier to give trades more room to develop.
Critical Design Philosophy: Unlike some systems that automatically adjust stops based on performance statistics, this strategy intentionally keeps stop-loss control in the user's hands. Automatic stop adjustment creates dangerous feedback loops—widening stops increases risk per contract, which forces position size reduction, which distorts performance metrics, leading to incorrect adaptations. Instead, the dashboard provides visibility into stop performance, empowering you to make informed manual adjustments when warranted. This preserves the integrity of the adaptive system while giving you the critical data needed for stop optimization.
Execution Kernel Architecture
The entry system offers three distinct execution modes to match trader preference and market character:
StopBreakout Mode: Places buy-stop orders above the prior bar's high (for longs) or sell-stop orders below the prior bar's low (for shorts), plus a 2-tick buffer. This ensures entries only occur when price confirms directional momentum by breaking recent structure. Ideal for trending and momentum-driven markets.
LimitPullback Mode: Places limit orders at a pullback price calculated as: Entry_Price = Close - (ATR × Pullback_Multiplier) for longs, or Close + (ATR × Pullback_Multiplier) for shorts. Default multiplier is 0.5 ATR. This waits for mean-reversion before entering in the signal direction, capturing better prices in volatile or oscillating markets.
MarketNextOpen Mode: Executes at market on the bar immediately following signal generation. This provides fastest execution but sacrifices the filtering effect of requiring price confirmation.
All pending entry orders include a configurable Time-To-Live (TTL, default 6 bars). If an order is not filled within the TTL period, it cancels automatically to prevent stale signals from executing in changed market conditions.
Professional Exit Management
The exit system implements a three-stage progression: initial stop loss, breakeven adjustment, and dynamic trailing stop.
Initial Stop Loss: Calculated as entry price ± (ATR × User_Stop_Multiplier × Volatility_Adjustment). Users have direct control via the Stop Loss ATR multiplier (default 1.25). The system then applies volatility regime adjustments: ×1.2 in high-volatility environments (stops automatically widen), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. This ensures stops adapt to market character while maintaining user control over baseline risk tolerance.
Breakeven Trigger: When profit reaches a configurable multiple of initial risk (default 1.0R), the stop loss automatically moves to breakeven (entry price). This locks in zero-loss status once the trade demonstrates favorable movement.
Trailing Stop Activation: When profit reaches the Trail_Trigger_R multiple (default 1.2R), the system cancels the fixed stop and activates a dynamic trailing stop. The trail uses Step and Offset parameters defined in R-multiples. For example, with Trail_Offset_R = 1.0 and Trail_Step_R = 1.5, the stop trails 1.0R behind price and moves in 1.5R increments. This captures extended moves while protecting accumulated profit.
Additional failsafes include maximum time-in-trade (exits after N bars if specified) and end-of-session flatten (automatically closes all positions X minutes before session end to avoid overnight exposure).
Core Calculation Methodology
Signal Component Scoring
Momentum Component:
- Calculates 14-period DMI (Directional Movement Index) with ADX strength filter (trending when ADX > 25)
- Computes three RSI timeframes: fast (7-period), medium (14-period), slow (21-period)
- Analyzes MACD (12/26/9) histogram for directional acceleration
- Bullish momentum: uptrend (DI+ > DI- with ADX > 25) + MACD histogram rising above zero + RSI fast between 50-80 = +1.6 score
- Bearish momentum: downtrend (DI- > DI+ with ADX > 25) + MACD histogram falling below zero + RSI fast between 20-50 = -1.6 score
- Score multiplies by volatility adjustment factor: ×0.8 in high volatility (momentum less reliable), ×1.2 in low volatility (momentum more persistent)
Structure Component:
- Identifies swing highs and lows using 10-bar pivot lookback on both sides
- Maintains most recent swing high as dynamic resistance, most recent swing low as dynamic support
- Detects breakouts: bullish when close crosses above resistance with prior bar below; bearish when close crosses below support with prior bar above
- Breakout score: ±1.0 for confirmed break
- Moving average alignment: +0.5 when price > SMA20 > SMA50 (bullish structure); -0.5 when price < SMA20 < SMA50 (bearish structure)
- Total structure range: -1.5 to +1.5
Volume Component:
- Calculates Volume Price Trend: VPT = Σ [(Close - Close ) / Close × Volume]
- Compares VPT to its 10-period EMA as signal line (similar to MACD logic)
- Computes 20-period volume moving average and standard deviation
- High volume event: current volume > (volume_average + 1× std_dev)
- Bullish volume: VPT > VPT_signal AND high_volume = +1.0
- Bearish volume: VPT < VPT_signal AND high_volume = -1.0
- No score if volume is not elevated (filters out low-conviction moves)
Reversal Component:
- Identifies extreme RSI conditions: RSI slow < 30 (oversold) or > 70 (overbought)
- Requires structural confluence: price at or below support level for bullish reversal; at or above resistance for bearish reversal
- Requires momentum shift: RSI fast must be rising (for bull) or falling (for bear) to confirm reversal in progress
- Bullish reversal: RSI < 30 AND price ≤ support AND RSI rising = +1.0
- Bearish reversal: RSI > 70 AND price ≥ resistance AND RSI falling = -1.0
Composite Score Calculation
Final_Score = (Momentum × Weight_M) + (Structure × Weight_S) + (Volume × Weight_V) + (Reversal × Weight_R)
Initial weights: Momentum = 1.0, Structure = 1.2, Volume = 0.8, Reversal = 0.6
These weights adapt after each trade based on component-specific performance as described above.
The system also applies directional bias adjustment: if recent long trades have significantly lower win rate than shorts, bullish scores multiply by 0.9 to reduce aggressive long entries. Vice versa for underperforming shorts.
Position Sizing Algorithm
The position sizing calculation incorporates multiple confidence factors and automatically scales to any futures contract:
1. Base risk amount = Account_Size × Base_Risk_Percent × Adaptive_Risk_Multiplier
2. Stop distance in price units = ATR × User_Stop_Multiplier × Volatility_Regime_Multiplier × Entry_Buffer
3. Risk per contract = Stop_Distance × Dollar_Per_Point (automatically detected from instrument)
4. Raw position size = Risk_Amount / Risk_Per_Contract
Then applies confidence scaling:
- Signal confidence = min(|Weighted_Score| / Min_Score_Threshold, 2.0) — higher scores receive larger size, capped at 2×
- Direction confidence = Long_Win_Rate (for bulls) or Short_Win_Rate (for bears)
- Type confidence = Win_Rate of dominant signal type (momentum/structure/volume/reversal)
- Total confidence = (Signal_Confidence + Direction_Confidence + Type_Confidence) / 3
Adjusted size = Raw_Size × Total_Confidence × Losing_Streak_Reduction
Losing streak reduction = 0.5 if losing_streak ≥ 5, otherwise 1.0
Universal Maximum Position Calculation: Instead of hardcoded limits per instrument, the system calculates maximum position size as: Max_Contracts = Account_Size / 25000, clamped between 1 and 10 contracts. This means a $50,000 account allows up to 2 contracts, a $100,000 account allows up to 4 contracts, regardless of which futures contract is being traded. This universal approach maintains consistent risk exposure across different instruments while preventing overleveraging.
Final size is rounded to integer and bounded by the calculated maximum.
Session and Risk Management System
Timezone-Aware Session Control
The strategy implements timezone-correct session filtering. Users specify session start hour, end hour, and timezone from 12 supported zones (New York, Chicago, Los Angeles, London, Frankfurt, Moscow, Tokyo, Hong Kong, Shanghai, Singapore, Sydney, UTC). The system converts bar timestamps to the selected timezone before applying session logic.
For split sessions (e.g., Asian session 18:00-02:00), the logic correctly handles time wraparound. Weekend trading can be optionally disabled (default: disabled) to avoid low-liquidity weekend price action.
Multi-Layer Risk Controls
Daily Loss Limit: Strategy ceases all new entries when daily P&L reaches negative threshold (default $2,000). This prevents catastrophic drawdown days. Resets at timezone-corrected day boundary.
Weekly Profit Target: Strategy ceases trading when weekly profit reaches target (default $10,000). This implements the professional principle of "take the win and stop pushing luck." Resets on timezone-corrected Monday.
Maximum Daily Trades: Hard cap on entries per day (default 20) to prevent overtrading during volatile conditions when many signals may generate.
Trailing Drawdown Guard: Optional prop-firm-style trailing stop on account equity. When enabled, if equity drops below (Peak_Equity - Trailing_DD_Amount), all trading halts. This simulates the common prop firm rule where exceeding trailing drawdown results in account termination.
All limits display status in the real-time dashboard, showing "MAX LOSS HIT", "WEEKLY TARGET MET", or "ACTIVE" depending on current state.
How To Use This Strategy
Initial Setup
1. Apply the strategy to your desired futures chart (tested on 5-minute through daily timeframes)
2. The strategy will automatically detect your instrument's specifications—no manual configuration needed for different contracts
3. Configure your account size and risk parameters in the Core Settings section
4. Set your trading session hours and timezone to match your availability
5. Adjust the Stop Loss ATR multiplier based on your risk tolerance (0.8-1.2 for tighter stops, 1.5-2.5 for wider stops)
6. Select your preferred entry execution mode (recommend StopBreakout for beginners)
7. Enable adaptation (recommended) or disable for fixed-parameter operation
8. Review the strategy's Properties in the Strategy Tester settings and verify commission/slippage match your broker's actual costs
The universal futures detection means you can switch between ES, NQ, CL, GC, ZB, or any other futures contract without changing any strategy parameters—the system will automatically adapt its calculations to each instrument's unique specifications.
Dashboard Interpretation
The strategy displays a comprehensive real-time dashboard in the top-right corner showing:
Market State Section:
- Trend: Shows UPTREND/DOWNTREND/CONSOLIDATING/NEUTRAL based on ADX and DMI analysis
- ADX Value: Current trend strength (>25 = strong trend, <20 = consolidating)
- Momentum: BULL/BEAR/NEUTRAL classification with current momentum score
- Volatility: HIGH/LOW/NORMAL regime with ATR percentage of price
Volume Profile Section (Large dashboard only):
- VPT Flow: Directional bias from volume analysis
- Volume Status: HIGH/LOW/NORMAL with relative volume multiplier
Performance Section:
- Daily P&L: Current day's profit/loss with color coding
- Daily Trades: Number of completed trades today
- Weekly P&L: Current week's profit/loss
- Target %: Progress toward weekly profit target
- Stop-Out Rate: Percentage of last 20 trades (or available trades if <20) that were stopped out. Includes all stop types: initial stops, breakeven stops, trailing stops, timeout exits, and EOD flattens. Color coded with actionable guidance:
- Green (<30%): Shows "TIGHTEN" guidance. Very few stop-outs suggests stops may be too loose or exceptional market conditions. Consider reducing Stop Loss ATR multiplier.
- Orange (30-65%): Shows "OK" guidance. Healthy stop-out rate indicating appropriate stop placement for current conditions.
- Red (>65%): Shows "WIDEN" guidance. Too many premature stop-outs. Consider increasing Stop Loss ATR multiplier to give trades more room.
- Status: Overall trading status (ACTIVE/MAX LOSS HIT/WEEKLY TARGET MET/FILTERS ACTIVE)
Adaptive Engine Section:
- Min Score: Current minimum threshold for trade entry (higher = more selective)
- Risk Mult: Current position sizing multiplier (adjusts with performance)
- Bars BTW: Current minimum bars required between trades
- Drawdown: Current drawdown percentage from equity peak
- Weights: M/S/V/R showing current component weightings
Win Rates Section:
- Type: Win rates for Momentum, Structure, Volume, Reversal signal types
- Direction: Win rates for Long vs Short trades
Color coding shows green for >50% win rate, red for <50%
Session Info Section:
- Session Hours: Active trading window with timezone
- Weekend Trading: ENABLED/DISABLED status
- Session Status: ACTIVE/INACTIVE based on current time
Signal Generation and Entry
The strategy generates entries when the weighted composite score exceeds the adaptive minimum threshold (initial value configurable, typically 1.5 to 2.5). Entries display as layered triangle markers on the chart:
- Long Signal: Three green upward triangles below the entry bar
- Short Signal: Three red downward triangles above the entry bar
Triangle tooltip shows the signal score and dominant signal type (MOMENTUM/STRUCTURE/VOLUME/REVERSAL).
Position Management and Stop Optimization
Once entered, the strategy automatically manages the position through its three-stage exit system. Monitor the Stop-Out Rate metric in the dashboard to optimize your stop placement:
If Stop-Out Rate is Green (<30%): You're rarely being stopped out. This could mean:
- Your stops are too loose, allowing trades to give back too much profit on reversals
- You're in an exceptional trending market where tight stops would work better
- Action: Consider reducing your Stop Loss ATR multiplier by 0.1-0.2 to tighten stops and lock in profits more efficiently
If Stop-Out Rate is Orange (30-65%): Optimal range. Your stops are appropriately sized for the strategy's risk-reward profile and current market volatility. No adjustment needed.
If Stop-Out Rate is Red (>65%): You're being stopped out too frequently. This means:
- Your stops are too tight for current market volatility
- Trades need more room to develop before reaching profit targets
- Action: Increase your Stop Loss ATR multiplier by 0.1-0.3 to give trades more breathing room
Remember: The stop-out rate calculation includes all exit types (initial stops, breakeven stops, trailing stops, timeouts, EOD flattens). A trade that reaches breakeven and gets stopped out at entry price counts as a stop-out, even though it didn't lose money. This is intentional—it indicates the stop placement didn't allow the trade to develop into profit.
Optimization Workflow
For traders wanting to customize the strategy for their specific instrument and timeframe:
Week 1-2: Run with defaults, adaptation enabled
Allow the system to execute at least 30-50 trades (the Learning Period plus additional buffer). Monitor which session periods, signal types, and market conditions produce the best results. Observe your stop-out rate—if it's consistently red or green, plan to adjust Stop Loss ATR multiplier after the learning period. Do not adjust parameters yet—let the adaptive system establish baseline performance data.
Week 3-4: Analyze adaptation behavior and optimize stops
Review the dashboard's adaptive weights and win rates. If certain signal types consistently show <40% win rate, consider slightly reducing their base weight. If a particular entry mode produces better fill quality and win rate, switch to that mode. If you notice the minimum score threshold has climbed very high (>3.0), market conditions may not suit the strategy's logic—consider switching instruments or timeframes.
Based on your Stop-Out Rate observations:
- Consistently <30%: Reduce Stop Loss ATR multiplier by 0.2-0.3
- Consistently >65%: Increase Stop Loss ATR multiplier by 0.2-0.4
- Oscillating between zones: Leave stops at default and let volatility regime adjustments handle it
Ongoing: Fine-tune risk and execution
Adjust the following based on your risk tolerance and account type:
- Base Risk Per Trade: 0.5% for conservative, 0.75% for moderate, 1.0% for aggressive
- Stop Loss ATR Multiplier: 0.8-1.2 for tight stops (scalping), 1.5-2.5 for wide stops (swing trading)
- Bars Between Trades: Lower (5-7) for more opportunities, higher (12-20) for more selective
- Entry Mode: Experiment between modes to find best fit for current market character
- Session Hours: Narrow to specific high-performance session windows if certain hours consistently underperform
Never adjust: Do not manually modify the adaptive weights, minimum score, or risk multiplier after the system has begun learning. These parameters are self-optimizing and manual interference defeats the adaptive mechanism.
Parameter Descriptions and Optimization Guidelines
Adaptive Intelligence Group
Enable Self-Optimization (default: true): Master switch for the adaptive learning system. When enabled, component weights, minimum score, risk multiplier, and trade spacing adjust based on realized performance. Disable to run the strategy with fixed parameters (useful for comparing adaptive vs non-adaptive performance).
Learning Period (default: 15 trades): Number of most recent trades to analyze for performance calculations. Shorter values (10-12) adapt more quickly to recent conditions but may overreact to variance. Longer values (20-30) produce more stable adaptations but respond slower to regime changes. For volatile markets, use shorter periods. For stable trends, use longer periods.
Adaptation Speed (default: 0.25): Controls the magnitude of parameter adjustments per learning cycle. Lower values (0.05-0.15) make gradual, conservative changes. Higher values (0.35-0.50) make aggressive adjustments. Faster adaptation helps in rapidly changing markets but increases parameter instability. Start with default and increase only if you observe the system failing to adapt quickly enough to obvious performance patterns.
Performance Memory (default: 100 trades): Maximum number of historical trades stored for analysis. This array size does not affect learning (which uses only Learning Period trades) but provides data for future analytics features including stop-out rate tracking. Higher values consume more memory but provide richer historical dataset. Typical users should not need to modify this.
Core Settings Group
Account Size (default: $50,000): Starting capital for position sizing calculations. This should match your actual account size for accurate risk per trade. The strategy uses this value to calculate dollar risk amounts and determine maximum position size (1 contract per $25,000).
Weekly Profit Target (default: $10,000): When weekly P&L reaches this value, the strategy stops taking new trades for the remainder of the week. This implements a "quit while ahead" rule common in professional trading. Set to a realistic weekly goal—20% of account size per week ($10K on $50K) is very aggressive; 5-10% is more sustainable.
Max Daily Loss (default: $2,000): When daily P&L reaches this negative threshold, strategy stops all new entries for the day. This is your maximum acceptable daily loss. Professional traders typically set this at 2-4% of account size. A $2,000 loss on a $50,000 account = 4%.
Base Risk Per Trade % (default: 0.5%): Initial percentage of account to risk on each trade before adaptive multiplier and confidence scaling. 0.5% is conservative, 0.75% is moderate, 1.0-1.5% is aggressive. Remember that actual risk per trade = Base Risk × Adaptive Risk Multiplier × Confidence Factors, so the realized risk will vary.
Trade Filters Group
Base Minimum Signal Score (default: 1.5): Initial threshold that composite weighted score must exceed to generate a signal. Lower values (1.0-1.5) produce more trades with lower average quality. Higher values (2.0-3.0) produce fewer, higher-quality setups. This value adapts automatically when adaptive mode is enabled, but the base sets the starting point. For trending markets, lower values work well. For choppy markets, use higher values.
Base Bars Between Trades (default: 9): Minimum bars that must elapse after an entry before another signal can trigger. This prevents overtrading and allows previous trades time to develop. Lower values (3-6) suit scalping on lower timeframes. Higher values (15-30) suit swing trading on higher timeframes. This value also adapts based on drawdown and losing streaks.
Max Daily Trades (default: 20): Hard limit on total trades per day regardless of signal quality. This prevents runaway trading during extremely volatile days when many signals may generate. For 5-minute charts, 20 trades/day is reasonable. For 1-hour charts, 5-10 trades/day is more typical.
Session Group
Session Start Hour (default: 5): Hour (0-23 format) when trading is allowed to begin, in the timezone specified. For US futures trading in Chicago time, session typically starts at 5:00 or 6:00 PM (17:00 or 18:00) Sunday evening.
Session End Hour (default: 17): Hour when trading stops and no new entries are allowed. For US equity index futures, regular session ends at 4:00 PM (16:00) Central Time.
Allow Weekend Trading (default: false): Whether strategy can trade on Saturday/Sunday. Most futures have low volume on weekends; keeping this disabled is recommended unless you specifically trade Sunday evening open.
Session Timezone (default: America/Chicago): Timezone for session hour interpretation. Select your local timezone or the timezone of your instrument's primary exchange. This ensures session logic aligns with your intended trading hours.
Prop Guards Group
Trailing Drawdown Guard (default: false): Enables prop-firm-style trailing maximum drawdown. When enabled, if equity drops below (Peak Equity - Trailing DD Amount), all trading halts for the remainder of the backtest/live session. This simulates rules used by funded trader programs where exceeding trailing drawdown terminates the account.
Trailing DD Amount (default: $2,500): Dollar amount of drawdown allowed from equity peak. If your equity reaches $55,000, the trailing stop sets at $52,500. If equity then drops to $52,499, the guard triggers and trading ceases.
Execution Kernel Group
Entry Mode (default: StopBreakout):
- StopBreakout: Places stop orders above/below signal bar requiring price confirmation
- LimitPullback: Places limit orders at pullback prices seeking better fills
- MarketNextOpen: Executes immediately at market on next bar
Limit Offset (default: 0.5x ATR): For LimitPullback mode, how far below/above current price to place the limit order. Smaller values (0.3-0.5) seek minor pullbacks. Larger values (0.8-1.2) wait for deeper retracements but may miss trades.
Entry TTL (default: 6 bars, 0=off): Bars an entry order remains pending before cancelling. Shorter values (3-4) keep signals fresh. Longer values (8-12) allow more time for fills but risk executing stale signals. Set to 0 to disable TTL (orders remain active indefinitely until filled or opposite signal).
Exits Group
Stop Loss (default: 1.25x ATR): Base stop distance as a multiple of the 14-period ATR. This is your primary risk control parameter and directly impacts your stop-out rate. Lower values (0.8-1.0) create tighter stops that reduce risk per trade but may get stopped out prematurely in volatile conditions—expect stop-out rates above 65% (red zone). Higher values (1.5-2.5) give trades more room to breathe but increase risk per contract—expect stop-out rates below 30% (green zone). The system applies additional volatility regime adjustments on top of this base: ×1.2 in high volatility environments (stops widen automatically), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. For scalping on lower timeframes, use 0.8-1.2. For swing trading on higher timeframes, use 1.5-2.5. Monitor the Stop-Out Rate metric in the dashboard and adjust this parameter to keep it in the healthy 30-65% orange zone.
Move to Breakeven at (default: 1.0R): When profit reaches this multiple of initial risk, stop moves to breakeven. 1.0R means after price moves in your favor by the distance you risked, you're protected at entry price. Lower values (0.5-0.8R) lock in breakeven faster. Higher values (1.5-2.0R) allow more room before protection.
Start Trailing at (default: 1.2R): When profit reaches this multiple, the fixed stop transitions to a dynamic trailing stop. This should be greater than the BE trigger. Values typically range 1.0-2.0R depending on how much profit you want secured before trailing activates.
Trail Offset (default: 1.0R): How far behind price the trailing stop follows. Tighter offsets (0.5-0.8R) protect profit more aggressively but may exit prematurely. Wider offsets (1.5-2.5R) allow more room for profit to run but risk giving back more on reversals.
Trail Step (default: 1.5R): How far price must move in profitable direction before the stop advances. Smaller steps (0.5-1.0R) move the stop more frequently, tightening protection continuously. Larger steps (2.0-3.0R) move the stop less often, giving trades more breathing room.
Max Bars In Trade (default: 0=off): Maximum bars allowed in a position before forced exit. This prevents trades from "going stale" during periods of no meaningful price action. For 5-minute charts, 50-100 bars (4-8 hours) is reasonable. For daily charts, 5-10 bars (1-2 weeks) is typical. Set to 0 to disable.
Flatten near Session End (default: true): Whether to automatically close all positions as session end approaches. Recommended to avoid carrying positions into off-hours with low liquidity.
Minutes before end (default: 5): How many minutes before session end to flatten. 5-15 minutes provides buffer for order execution before the session boundary.
Visual Effects Configuration Group
Dashboard Size (default: Normal): Controls information density in the dashboard. Small shows only critical metrics (excludes stop-out rate). Normal shows comprehensive data including stop-out rate. Large shows all available metrics including weights, session info, and volume analysis. Larger sizes consume more screen space but provide complete visibility.
Show Quantum Field (default: true): Displays animated grid pattern on the chart indicating market state. Disable if you prefer cleaner charts or experience performance issues on lower-end hardware.
Show Wick Pressure Lines (default: true): Draws dynamic lines from bars with extreme wicks, indicating potential support/resistance or liquidity absorption zones. Disable for simpler visualization.
Show Morphism Energy Beams (default: true): Displays directional beams showing momentum energy flow. Beams intensify during strong trends. Disable if you find this visually distracting.
Show Order Flow Clouds (default: true): Draws translucent boxes representing volume flow bullish/bearish bias. Disable for cleaner price action visibility.
Show Fractal Grid (default: true): Displays multi-timeframe support/resistance levels based on fractal price structure at 10/20/30/40/50 bar periods. Disable if you only want to see primary pivot levels.
Glow Intensity (default: 4): Controls the brightness and thickness of visual effects. Lower values (1-2) for subtle visualization. Higher values (7-10) for maximum visibility but potentially cluttered charts.
Color Theme (default: Cyber): Visual color scheme. Cyber uses cyan/magenta futuristic colors. Quantum uses aqua/purple. Matrix uses green/red terminal style. Aurora uses pastel pink/purple gradient. Choose based on personal preference and monitor calibration.
Show Watermark (default: true): Displays animated watermark at bottom of chart with creator credit and current P&L. Disable if you want completely clean charts or need screen space.
Performance Characteristics and Best Use Cases
Optimal Conditions
This strategy performs best in markets exhibiting:
Trending phases with periodic pullbacks: The combination of momentum and structure components excels when price establishes directional bias but provides retracement opportunities for entries. Markets with 60-70% trending bars and 30-40% consolidation produce the highest win rates.
Medium to high volatility: The ATR-based stop sizing and dynamic risk adjustment require sufficient price movement to generate meaningful profit relative to risk. Instruments with 2-4% daily ATR relative to price work well. Extremely low volatility (<1% daily ATR) generates too many scratch trades.
Clear volume patterns: The VPT volume component adds significant edge when volume expansions align with directional moves. Instruments and timeframes where volume data reflects actual transaction flow (versus tick volume proxies) perform better.
Regular session structure: Futures markets with defined opening and closing hours, consistent liquidity throughout the session, and clear overnight/day session separation allow the session controls and time-based failsafes to function optimally.
Sufficient liquidity for stop execution: The stop breakout entry mode requires that stop orders can fill without significant slippage. Highly liquid contracts work better than illiquid instruments where stop orders may face adverse fills.
Suboptimal Conditions
The strategy may struggle with:
Extreme chop with no directional persistence: When ADX remains below 15 for extended periods and price oscillates rapidly without establishing trends, the momentum component generates conflicting signals. Win rate typically drops below 40% in these conditions, triggering the adaptive system to increase minimum score thresholds until conditions improve. Stop-out rates may also spike into the red zone.
Gap-heavy instruments: Markets with frequent overnight gaps disrupt the continuous price assumptions underlying ATR stops and EMA-based structure analysis. Gaps can also cause stop orders to fill at prices far from intended levels, distorting stop-out rate metrics.
Very low timeframes with excessive noise: On 1-minute or tick charts, the signal components react to micro-structure noise rather than meaningful price swings. The strategy works best on 5-minute through daily timeframes where price movements reflect actual order flow shifts.
Extended low-volatility compression: During historically low volatility periods, profit targets become difficult to reach before mean-reversion occurs. The trail offset, even when set to minimum, may be too wide for the compressed price environment. Stop-out rates may drop to green zone indicating stops should be tightened.
Parabolic moves or climactic exhaustion: Vertical price advances or selloffs where price moves multiple ATRs in single bars can trigger momentum signals at exhaustion points. The structure and reversal components attempt to filter these, but extreme moves may override normal logic.
The adaptive learning system naturally reduces signal frequency and position sizing during unfavorable conditions. If you observe multiple consecutive days with zero trades and "FILTERS ACTIVE" status, this indicates the strategy has self-adjusted to avoid poor conditions rather than forcing trades.
Instrument Recommendations
Emini Index Futures (ES, MES, NQ, MNQ, YM, RTY): Excellent fit. High liquidity, clear volatility patterns, strong volume signals, defined session structure. These instruments have been extensively tested and the universal detection handles all contract specifications automatically.
Micro Index Futures (MES, MNQ, M2K, MYM): Excellent fit for smaller accounts. Same market characteristics as the standard eminis but with reduced contract sizes allowing proper risk management on accounts below $50,000.
Energy Futures (CL, NG, RB, HO): Good to mixed fit. Crude oil (CL) works well due to strong trends and reasonable volatility. Natural gas (NG) can be extremely volatile—consider reducing Base Risk to 0.3-0.4% and increasing Stop Loss ATR multiplier to 1.8-2.2 for NG. The strategy automatically detects the $10/tick value for CL and adjusts position sizing accordingly.
Metal Futures (GC, SI, HG, PL): Good fit. Gold (GC) and silver (SI) exhibit clear trending behavior and work well with the momentum/structure components. The strategy automatically handles the different point values ($100/point for gold, $5,000/point for silver).
Agricultural Futures (ZC, ZS, ZW, ZL): Good fit. Grain futures often trend strongly during seasonal periods. The strategy handles the unique tick sizes (1/4 cent increments) and point values ($50/point for corn/wheat, $60/point for soybeans) automatically.
Treasury Futures (ZB, ZN, ZF, ZT): Good fit for trending rates environments. The strategy automatically handles the fractional tick sizing (32nds for ZB/ZN, halves of 32nds for ZF/ZT) through the universal detection system.
Currency Futures (6E, 6J, 6B, 6A, 6C): Good fit. Major currency pairs exhibit smooth trending behavior. The strategy automatically detects point values which vary significantly ($12.50/tick for 6E, $12.50/tick for 6J, $6.25/tick for 6B).
Cryptocurrency Futures (BTC, ETH, MBT, MET): Mixed fit. These markets have extreme volatility requiring parameter adjustment. Increase Base Risk to 0.8-1.2% and Stop Loss ATR multiplier to 2.0-3.0 to account for wider stop distances. Enable 24-hour trading and weekend trading as these markets have no traditional sessions.
The universal futures compatibility means you can apply this strategy to any of these markets without code modification—simply open the chart of your desired contract and the strategy will automatically configure itself to that instrument's specifications.
Important Disclaimers and Realistic Expectations
This is a sophisticated trading strategy that combines multiple analytical methods within an adaptive framework designed for active traders who will monitor performance and market conditions. It is not a "set and forget" fully automated system, nor should it be treated as a guaranteed profit generator.
Backtesting Realism and Limitations
The strategy includes realistic trading costs and execution assumptions:
- Commission: $0.62 per contract per side (accurate for many retail futures brokers)
- Slippage: 1 tick per entry and exit (conservative estimate for liquid futures)
- Position sizing: Realistic risk percentages and maximum contract limits based on account size
- No repainting: All calculations use confirmed bar data only—signals do not change retroactively
However, backtesting cannot fully capture live trading reality:
- Order fill delays: In live trading, stop and limit orders may not fill instantly at the exact tick shown in backtest
- Volatile periods: During high volatility or low liquidity (news events, rollover days, pre-holidays), slippage may exceed the 1-tick assumption significantly
- Gap risk: The backtest assumes stops fill at stop price, but gaps can cause fills far beyond intended exit levels
- Psychological factors: Seeing actual capital at risk creates emotional pressures not present in backtesting, potentially leading to premature manual intervention
The strategy's backtest results should be viewed as best-case scenarios. Real trading will typically produce 10-30% lower returns than backtest due to the above factors.
Risk Warnings
All trading involves substantial risk of loss. The adaptive learning system can improve parameter selection over time, but it cannot predict future price movements or guarantee profitable performance. Past wins do not ensure future wins.
Losing streaks are inevitable. Even with a 60% win rate, you will encounter sequences of 5, 6, or more consecutive losses due to normal probability distributions. The strategy includes losing streak detection and automatic risk reduction, but you must have sufficient capital to survive these drawdowns.
Market regime changes can invalidate learned patterns. If the strategy learns from 50 trades during a trending regime, then the market shifts to a ranging regime, the adapted parameters may initially be misaligned with the new environment. The system will re-adapt, but this transition period may produce suboptimal results.
Prop firm traders: understand your specific rules. Every prop firm has different rules regarding maximum drawdown, daily loss limits, consistency requirements, and prohibited trading behaviors. While this strategy includes common prop guardrails, you must verify it complies with your specific firm's rules and adjust parameters accordingly.
Never risk capital you cannot afford to lose. This strategy can produce substantial drawdowns, especially during learning periods or market regime shifts. Only trade with speculative capital that, if lost, would not impact your financial stability.
Recommended Usage
Paper trade first: Run the strategy on a simulated account for at least 50 trades or 1 month before committing real capital. Observe how the adaptive system behaves, identify any patterns in losing trades, monitor your stop-out rate trends, and verify your understanding of the entry/exit mechanics.
Start with minimum position sizing: When transitioning to live trading, reduce the Base Risk parameter to 0.3-0.4% initially (vs 0.5-1.0% in testing) to reduce early impact while the system learns your live broker's execution characteristics.
Monitor daily, but do not micromanage: Check the dashboard daily to ensure the strategy is operating normally and risk controls have not triggered unexpectedly. Pay special attention to the Stop-Out Rate metric—if it remains in the red or green zones for multiple days, adjust your Stop Loss ATR multiplier accordingly. However, resist the urge to manually adjust adaptive weights or disable trades based on short-term performance. Allow the adaptive system at least 30 trades to establish patterns before making manual changes.
Combine with other analysis: While this strategy can operate standalone, professional traders typically use systematic strategies as one component of a broader approach. Consider using the strategy for trade execution while applying your own higher-timeframe analysis or fundamental view for trade filtering or sizing adjustments.
Keep a trading journal: Document each week's results, note market conditions (trending vs ranging, high vs low volatility), record stop-out rates and any Stop Loss ATR adjustments you made, and document any manual interventions. Over time, this journal will help you identify conditions where the strategy excels versus struggles, allowing you to selectively enable or disable trading during certain environments.
Technical Implementation Notes
All calculations execute on closed bars only (`calc_on_every_tick=false`) ensuring that signals and values do not repaint. Once a bar closes and a signal generates, that signal is permanent in the history.
The strategy uses fixed-quantity position sizing (`default_qty_type=strategy.fixed, default_qty_value=1`) with the actual contract quantity determined by the position sizing function and passed to the entry commands. This approach provides maximum control over risk allocation.
Order management uses Pine Script's native `strategy.entry()` and `strategy.exit()` functions with appropriate parameters for stops, limits, and trailing stops. All orders include explicit from_entry references to ensure they apply to the correct position.
The adaptive learning arrays (trade_returns, trade_directions, trade_types, trade_hours, trade_was_stopped) are maintained as circular buffers capped at PERFORMANCE_MEMORY size (default 100 trades). When a new trade closes, its data is added to the beginning of the array using `array.unshift()`, and the oldest trade is removed using `array.pop()` if capacity is exceeded. The stop-out tracking system analyzes the trade_was_stopped array to calculate the rolling percentage displayed in the dashboard.
Dashboard rendering occurs only on the confirmed bar (`barstate.isconfirmed`) to minimize computational overhead. The table is pre-created with sufficient rows for the selected dashboard size and cells are populated with current values each update.
Visual effects (fractal grid, wick pressure, morphism beams, order flow clouds, quantum field) recalculate on each bar for real-time chart updates. These are computationally intensive—if you experience chart lag, disable these visual components. The core strategy logic continues to function identically regardless of visual settings.
Timezone conversions use Pine Script's built-in timezone parameter on the `hour()`, `minute()`, and `dayofweek()` functions. This ensures session logic and daily/weekly resets occur at correct boundaries regardless of the chart's default timezone or the server's timezone.
The universal futures detection queries `syminfo.mintick` and `syminfo.pointvalue` on each strategy initialization to obtain the current instrument's specifications. These values remain constant throughout the strategy's execution on a given chart but automatically update when the strategy is applied to a different instrument.
The strategy has been tested on TradingView across timeframes from 5-minute through daily and across multiple futures instrument types including equity indices, energy, metals, agriculture, treasuries, and currencies. It functions identically on all instruments due to the percentage-based risk model and ATR-relative calculations which adapt automatically to price scale and volatility, combined with the universal futures detection system that handles contract-specific specifications.
Trend Pullback System```{"variant":"standard","id":"36492","title":"Trend Pullback System Description"}
Trend Pullback System is a price-action trend continuation model that looks to enter on pullbacks, not breakouts. It’s designed to find high-quality long/short entries inside an already established trend, place the stop at meaningful structure, trail that stop as structure evolves, and warn you when the trade thesis is no longer valid.
Developed by: Mohammed Bedaiwi
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HOW IT WORKS
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1. Trend Detection
• The strategy defines overall bias using moving averages.
• Bullish environment (“uptrend”): price above the slower MA, fast MA above slow MA, and the slow MA is sloping up.
• Bearish environment (“downtrend”): price below the slower MA, fast MA below slow MA, and the slow MA is sloping down.
This prevents trading against chop and focuses on continuation moves in the dominant direction.
2. Pullback + Re-entry Logic
• The script waits for price to pull back into structure (support in an uptrend, resistance in a downtrend), and then push back in the direction of the main trend.
• That “push back” is the setup trigger. We don’t chase the first breakout candle — we buy/sell the retest + resume.
3. Structural Levels (“Diamonds”)
• Green diamond (below bar): bullish pivot low formed while the trend is bullish. This marks defended support.
- Use it as a re-entry zone for longs.
- Use it to trail a stop higher when you’re already long.
- Shorts can take profit here because buyers stepped in.
• Red diamond (above bar): bearish pivot high formed while the trend is bearish. This marks defended resistance.
- Use it as a re-entry zone for shorts.
- Use it to trail a stop lower when you’re already short.
- Longs can take profit here because sellers stepped in.
4. Entry Signals
• BUY arrow (green triangle up under the candle, text like “BUY” / “BUY Zone”):
- LongSetup is true.
- Trend is bullish or turning bullish.
- Price just bounced off recent defended support (green diamond) and reclaimed short-term momentum.
Meaning: enter long here or cover/exit shorts.
• SELL arrow (red triangle down above the candle):
- ShortSetup is true.
- Trend is bearish or turning bearish.
- Price just rolled down from defended resistance (red diamond) and lost short-term momentum.
Meaning: enter short here or take profit on longs.
These are the primary trade entries. They are meant to be actionable.
5. Weak Setups (“W” in yellow)
• Yellow triangle with “W”:
- A possible long/short idea is trying to form, BUT the higher-timeframe confirmation is not fully there yet.
- Think of it as early pressure / early caution, not a full signal.
• You usually watch these areas rather than jumping in immediately.
6. Exit Warning (orange “EXIT” label above a bar)
• The strategy will raise an EXIT marker when you’re in a trade and the *opposite* side just produced a confirmed setup.
- You’re short and a valid longSetup appears → EXIT.
- You’re long and a valid shortSetup appears → EXIT.
• This is basically: “Close or reduce — the other side just took control.”
• It’s not just a trailing stop hit; it’s a regime flip warning.
7. Stop, Target, and Trailing
• On every new setup, the script records:
- Initial stop: recent swing beyond the defended level (below support for longs, above resistance for shorts).
- Initial target: recent opposing swing.
• While you’re in position, if new confirming diamonds print in your favor, the stop can trail toward the new defended level.
• This creates structure-based risk management (not just fixed % or ATR).
8. Reference Levels
• The strategy also plots prior higher-timeframe closes (last week’s close, last month’s close, last year’s close). These can behave as magnets or stall points.
• They’re helpful for take-profit timing and for reading “are we trading above or below last month’s close?”
9. Momentum Panel (hidden by default)
• Internally, the script calculates an SMI-style momentum oscillator with overbought/oversold zones.
• This is optional visual confirmation and does not drive the core entry/exit logic.
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WHAT A TRADE LOOKS LIKE IN REAL PRICE ACTION
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Early warning
• Yellow W + red diamonds + red down arrows = “This is getting weak. Short setups are here.”
• You may also see something like “My Short Entry Id.” That’s where the short side actually engages.
Bearish follow-through, then exhaustion
• Price bleeds down.
• Then the orange EXIT appears.
→ Translation: “If you’re still short, close it. Buyers are stepping in hard. Risk of reversal is now high.”
Regime flip
• Right after EXIT, multiple green BUY arrows fire together (“BUY”, “BUYZone”).
• That’s the true long trigger.
→ This is where you either enter long or flip from short to long.
Expansion leg
• After that flip, price rips up for multiple candles / days / weeks.
• While it runs:
- Green diamonds appear under pullbacks → “dip buy zones / trail stop up here.”
- More BUY arrows show on minor pullbacks → continuation long / scale adds.
Distribution / topping
• Later, you start seeing new yellow W triangles again near local highs. That’s your “careful, this might be topping” warning.
• You finally get a hard red candle, and green diamonds stop stacking.
→ That’s where you tighten risk, scale out, or assume the move is mature.
In plain terms, the model is doing the following for you:
• It puts you short during weakness.
• It tells you when to get OUT of the short.
• It flips you long right as control changes.
• It gives you a structure-based trail the whole way up.
• It warns you again when momentum at the top starts cracking.
That is exactly how the logic was designed.
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QUICK INTERPRETATION CHEAT SHEET
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🔻 Red triangle + “Short Entry” near a red diamond
→ Short entry zone (or take profit on a long).
🟥 Red diamond above bar
→ Sellers defended here. Treat it as resistance. Good place to trail short stops just above that level. Avoid chasing longs straight into it.
🟨 Yellow W
→ Attention only. Early pressure / possible turn. Not fully confirmed.
🟧 EXIT (orange label)
→ The opposite side just printed a real setup. Close the old idea (cover shorts if you’re short, exit longs if you’re long). Thesis invalid.
🟩 Burst of green BUY triangles after EXIT
→ Long entry. Also a “cover shorts now” alert. This is the core money entry in bullish reversals.
💎 Green diamond below bar
→ Bulls defended that level. Good for trailing your long stop up, and good “buy the dip in trend” locations.
📈 Blue / teal MAs stacked and rising
→ Confirmed bullish structure. You’re in trend continuation mode, so dips are opportunities, not automatic exits.
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COLOR / SHAPE KEY
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• Green triangle up (“BUY”, “BUY Zone”):
Long entry / cover shorts / continuation long trigger.
• Red triangle down:
Short entry / take profit on longs / continuation short trigger.
• Orange “EXIT” label:
Opposite side just fired a real setup. The previous trade thesis is now invalid.
• Green diamond below price:
Bullish defended support in an uptrend. Use for dip buys, trailing stops on longs, and objective cover zones for shorts.
• Red diamond above price:
Bearish defended resistance in a downtrend. Use for re-entry shorts, trailing stops on shorts, and objective scale-out zones for longs.
• Yellow “W”:
Weak / early potential setup. Watch it, don’t blindly trust it.
• Moving average bands (fast MA, slow MA, Hull MA):
When stacked and rising, bullish control. When stacked and falling, bearish control.
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INTENT
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This system is built to:
• Trade with momentum, not against it.
• Enter on pullbacks into proven structure, not chase stretched breakouts.
• Automate stop/target logic around actual defended swing levels.
• Warn you when the other side takes over so you don’t give back gains.
Typical usage:
1. In an uptrend, wait for price to pull back, print a green diamond (support proved), then take the first BUY arrow that fires.
2. In a downtrend, wait for a bounce into resistance, print a red diamond (sellers proved), then take the first SELL arrow that fires.
3. Respect EXIT when it appears — that’s the model saying “this trade is done.”
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DISCLAIMER
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This script is for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security, cryptoasset, or derivative. Markets carry risk. Past performance does not guarantee future results. You are fully responsible for your own decisions, position sizing, risk management, and compliance with all applicable laws and regulations.
HEK Dynamic Price Channel StrategyHEK Dynamic Price Channel Strategy
Concept
The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium.
Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions.
How It Works
When the price reacts to the midline, the channel bands automatically reposition themselves.
Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum.
This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality.
Advantages
✅ Maintains trend continuity while avoiding overtrading.
✅ Automatically adapts to changing volatility conditions.
✅ Detects early signals of short- and mid-term trend reversals.
Applications
Directional confirmation in spot and futures markets.
A supporting tool in channel breakout strategies.
Identifying price consolidation and equilibrium zones.
Note
This strategy is intended for educational and research purposes only.
It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions.
© HEK — Adaptive Channel Approach on Dynamic Market Structures
Iriza4 -DAX EMA+HULL+ADX TP40 SL205 MIN SKALP. Additional filters improve accuracy: the strategy blocks trades after too many consecutive bullish or bearish candles (streak filter) and ignores signals when price is too far from the EMA (measured by ATR distance).
Each position uses a fixed risk-to-reward ratio of 1 : 2 with clear stop-loss and take-profit targets, without partial exits or breakevens. The goal is to identify clean pullbacks inside strong trends and filter out late or exhausted entries
AIBTC Automated Trading Strategy🧠 AIBTC Automated Trading Strategy
Overview:
The AIBTC Automated Trading Strategy is a fully autonomous system designed for 4-hour timeframes (4H). It dynamically identifies support and resistance levels based on price action, and automatically executes trades when valid breakouts occur above resistance or below support. The system adapts in real time to changing market volatility, ensuring stable performance across different market conditions.
⚙️ Strategy Logic
Dynamic Support & Resistance Detection
The strategy uses an adaptive Pivot Point algorithm that adjusts parameters according to market volatility (ATR) and price deviation (Standard Deviation).
When volatility increases, the algorithm automatically widens its detection range and recalibrates channel width for better accuracy.
All support and resistance levels are detected dynamically — no manual configuration is required.
Trend & Volatility Filtering
The system applies ADX (Average Directional Index) to measure trend strength.
When ADX > 25, only strong levels are considered valid to avoid noise during weak trends.
ATR-based volatility adjustments automatically optimize lookback periods and detection sensitivity.
Breakout Signal Detection
A long position is triggered when price breaks above resistance with a valid breakout margin (default filter: 0.1%).
A short position is triggered when price breaks below support with the same breakout filter applied.
This breakout filter effectively minimizes false breakouts and improves signal quality.
Fully Automated Execution
The system is designed for both backtesting and live simulation.
All buy/sell entries are executed automatically without manual input once conditions are met.
🕒 Recommended Timeframe
4-hour (4H) candles
Suitable for short-to-medium term swing trading, balancing signal precision and trade frequency.
📊 Key Features
✅ Fully Automated — Executes long/short positions on valid breakouts
✅ Adaptive Parameters — Automatically adjusts to changing volatility
✅ Trend-Aware Filtering — Uses ADX to avoid false signals in ranging markets
✅ Multi-Asset Compatibility — Works on BTC, ETH, or any high-liquidity instrument
⚠️ Disclaimer
This strategy is a technical and algorithmic tool, not financial advice.
Always backtest and simulate before using it on live markets.
During periods of extreme volatility, signals may delay or show false breakouts — consider using stop-loss mechanisms accordingly.
One For All Strategy by Anson🏆 Exclusive Indicator: One For All Strategy
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📈 Works for stocks, forex, crypto, indices
📈 Easy to use, real-time alerts, no repaint
📈 No grid, no martingale, no hedging
📈 One position at a time
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One For All Strategy by Anson
A multi-indicator TradingView strategy designed to identify long and short trading opportunities by combining trend-following and momentum signals, paired with risk management rules to guide entries and exits.
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Core Logic & Key Indicator:
X Moving Average: A proprietary adaptive moving average that adjusts its responsiveness to price changes based on market volatility. It uses an efficiency ratio to modify its smoothing behavior—adapting to whether the market is trending or ranging. Users can toggle a setting to let this ratio dynamically adjust the indicator’s sensitivity or use a fixed smoothing factor.
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Entry Conditions:
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Long Entry: Triggered when momentum signals strength, price action aligns with a broader upward trend, the X MA indicates short-term upward momentum, and a minimum number of bars have passed since the last trade (to prevent overtrading).
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Short Entry: Triggered when momentum signals weakness, price action aligns with a broader downward trend, the X MA indicates short-term downward momentum, and a minimum number of bars have passed since the last trade.
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Exit Conditions:
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Trailing Stop: Activates after a position has been open for a set number of bars (to avoid premature exits). A trailing stop—based on a percentage of the entry price—locks in profits as the trade moves favorably, adjusting dynamically to protect gains.
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Additional Features:
Visualisation: Overlays the X MA (orange line) and price (semi-transparent blue) on the chart for clear signal tracking.
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See the author's instructions on the right to learn how to get access to the strategy.
EMA 9/50 News Confirmation Strategy v3 (Trend Aligned 3 bMin) “EMA 9/50 crossover strategy with trend filter and ATR-based targets”)
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
SB LONG ENTRY/EXITBASED on HULL slope average. ISN'T IT VERY ROBUST?
Very good for daily, weekly and monthly timeframes. Stocks especially.....
I prefer it without optonal stop loss on other position protection stops.
Wonderful both equal weight position or with a D'alembert style weighting of positions....
Hold the Hull period parameter between 30 and 60 or more, but it's not so sensitive to this optimization.
All the best,
Sandro Bisotti
Entry / exit zones (only long positions)Great and simple helping tool to find good entry/exit point for mid/long term trading on stocks especially but also indexes and other..... Good on daily timeframe, but better with weekly and monthly. Based on Hull average slope. Hold the average period value among 30 and 50 or more. I prefer the version WITHOUT stop loss and other exit rules (optional).
All the best and good trading!
SB
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
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TAGS:
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trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
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CATEGORY:
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Strategies
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CHART SETUP RECOMMENDATIONS:
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For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
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COMPLIANCE NOTES:
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✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
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Hull Suite Strategy with Time FilterThis script is a Hull Moving Average–based trend system designed to visualize market direction and filter signals during specific trading hours.
It features:
Dual HMA bands for smoother trend detection
Color changes based on slope to highlight momentum
Optional time filter for signal control within session hours
Compact buy/sell signal markers
You can adjust HMA lengths, time filters, and visual options from the settings panel.
This script is intended for educational and analytical purposes only — not financial advice.
