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ADX Dynamic Zone Inside the SuperTrend with Support / ResistantI like Simple Strategy and just code one using super trend and ADX But like All super trend strategy buy and sell signal most of the time are to late So I am using the super trend like indicator for trend direction and ADX Dynamic buy or sell zone for pull back and if direction is ok we get in trade but only when we have support for long or resistant for short Take profit is fix % and stop is Trailing stop There is A choice if you want to use fixed sum for the trades or increase the size of the trade after # of losing trades The increase of the size is working like D'Alembert System Thanks to Trading view and pinecoders.com for the build in indicators and code If any Questions Let Me Know Happy Trading
กลยุทธ์ Pine Script®
โดย fullmax
3
Improved EMA Trend + ATR Strategy with ArrowsThis strategy is built around a simple idea: strong directional moves often begin after periods of low volatility. Instead of chasing trends late, it waits for price compression and then trades the breakout when expansion begins. The approach combines volatility structure and trend alignment to reduce random entries. Core Concept Markets cycle between quiet phases and expansion phases. When volatility contracts, it often leads to a stronger move once price breaks out of that range. This strategy attempts to capture that transition. How It Works 1. Volatility Compression Detection A squeeze condition is identified when Bollinger Bands contract inside Keltner Channels. This signals reduced volatility. 2. Squeeze Release The strategy waits for volatility to expand again. Trades are only considered when the squeeze ends. 3. Breakout Confirmation Entries occur when price breaks above or below the Bollinger Bands after the squeeze release. 4. Trend Alignment A long-term EMA is used to filter direction: Above EMA → bullish bias Below EMA → bearish bias This helps reduce counter-trend trades. 5. Risk Management Stop-loss and take-profit levels are based on ATR. This allows exits to adapt to current market volatility. A configurable risk-to-reward ratio defines profit targets. Key Features Structured volatility-based entries Trend confirmation filter ATR-based dynamic risk control Commission and slippage included for realistic testing No repainting logic Best Conditions This type of strategy tends to perform better during: Volatility expansion phases Strong directional markets Assets that experience compression before breakouts It may underperform in slow, range-bound environments. Important Notes This strategy is designed for research and backtesting purposes. Performance will vary across different markets and timeframes. Always evaluate across multiple conditions before considering live deployment.
กลยุทธ์ Pine Script®
โดย AIScripts
EURUSD Volatility Compression Breakout v1.0 Overview The EURUSD Volatility Compression Breakout (VCB Pro) is a momentum-volatility hybrid indicator designed to detect explosive breakout moves after periods of market compression. Financial markets move in cycles: 🔹 Expansion → 🔹 Contraction → 🔹 Expansion This indicator identifies when the market is “coiling” (low volatility compression) and signals when real expansion begins — filtering out weak or fake breakouts. It is optimized for EURUSD intraday volatility behavior, especially during London and New York sessions. ⚙️ How The Indicator Works (Step-By-Step Logic) 1️⃣ Trend Bias Filter (Directional Context) The indicator uses a 100 EMA to define directional bias: • Price above EMA → Bullish environment • Price below EMA → Bearish environment This prevents counter-trend breakout trades and increases probability alignment with macro flow. 2️⃣ Volatility Compression Detection The system measures compression using: • Bollinger Band Width • ATR (Average True Range) Compression is detected when: • Bollinger Bands narrow significantly • ATR falls below its moving average This indicates: ✔ Reduced volatility ✔ Liquidity building ✔ Energy accumulation ✔ Market “coiling” The background turns blue during compression phases to visually highlight pressure zones. 3️⃣ Expansion Detection After compression, the indicator waits for: • ATR spike (volatility expansion) • Large candle body (momentum confirmation) This ensures the breakout is driven by strong orderflow — not random price noise. 4️⃣ Breakout Confirmation A breakout signal triggers only when: ✔ Previous candle was in compression ✔ Current candle shows expansion ✔ Price closes outside Bollinger Bands ✔ Direction aligns with EMA trend This 4-layer confirmation drastically reduces false signals. 📊 What The Signals Mean 🟢 BREAKOUT BUY Indicates: • Volatility expansion upward • Bullish momentum confirmed • Price breaking upper range • Trend aligned Best used during: • London Open • NY Open • High impact session volatility 🔴 BREAKOUT SELL Indicates: • Volatility expansion downward • Bearish momentum confirmed • Price breaking lower range • Trend aligned Best used during: • News volatility • Session opens • Post-compression breakdowns 💎 Key Benefits of This Indicator ✅ 1. Detects Explosive Moves Early It identifies the transition from quiet accumulation to aggressive expansion. ✅ 2. Filters Fake Breakouts Most breakout traders fail because they trade inside compression. This indicator waits for confirmed expansion. ✅ 3. Trend-Aligned Entries Prevents emotional counter-trend trading. ✅ 4. Works Extremely Well on EURUSD EURUSD often compresses during Asian session and expands during London. This indicator is structured around that behavior. ✅ 5. Non-Repainting Logic Signals only confirm after candle close. No repainting. No hindsight bias. ✅ 6. Clean & Professional Chart No clutter. Minimal shapes. Clear background compression zones. 🔥 Final Summary This is not a basic Bollinger Band breakout. ✔ Volatility cycle ✔ Momentum shift ✔ Trend alignment ✔ Pressure build-up ✔ Real expansion It is designed to trade movement — not noise.
อินดิเคเตอร์ Pine Script®
โดย Mentor_Michael03
Impulse MACD StrategyImpulse MACD Strategy This strategy is built directly on the original "Impulse MACD " indicator. Original author & script: **LazyBear** (published April 2015) Link: The core Impulse MACD logic — including SMMA on high/low, ZLEMA on HLC3, impulse zone filtering (md calculation), color coding, and signal/histogram — is reused from LazyBear's open-source code with full credit. **Significant enhancements added in this version:** - Converted to a full automated **strategy** with long/short entries - Entries only on valid phase changes after prior extension > user threshold (pullback filter) - Optional SuperTrend trend filter - EMA-based exits + automatic break-even stop after N bars - Entry labels and comprehensive performance stats table (trades, win rate, avg win/loss, net profit) This adds substantial new logic, risk management, and usability beyond the original indicator. Always backtest carefully — no guarantees of future performance. Use at your own risk. Full credit and thanks to **LazyBear** for the innovative Impulse MACD concept that inspired this work. Happy trading! Aaron
กลยุทธ์ Pine Script®
โดย aaronrileycheer
TJR BOS (CHOCH) - Real time SwingsThis script displays BOS using TJR-style logic. Unlike traditional BOS indicators, the BOS shown here represents CHOCH (Change of Character). A BOS prints when: • Price closes ABOVE the previous swing high during a downtrend • Price closes BELOW the previous swing low during an uptrend Trend direction is determined using market structure: • Uptrend → Higher Highs + Higher Lows • Downtrend → Lower Highs + Lower Lows The indicator continuously updates swing highs and lows in real time.
อินดิเคเตอร์ Pine Script®
โดย marcelimac6
Precision Confluence Trading Strategy [JOAT]Precision Confluence Trading Strategy Introduction The Precision Confluence Trading Strategy is an open-source algorithmic trading system that combines Central Pivot Range (CPR) analysis, Hull Moving Average (HMA) ribbon alignment, WaveTrend oscillator signals, multi-oscillator divergence detection, ADX trend strength, volume confirmation, Smart Money Concepts (FVG, Order Blocks, Liquidity Sweeps), and multi-timeframe analysis into a comprehensive confluence-based strategy. This mashup creates an institutional-grade trading system designed to identify high-probability setups where multiple independent analytical frameworks simultaneously signal the same direction. The strategy addresses a fundamental challenge in algorithmic trading: single-factor systems produce too many false signals and lack robustness across different market conditions. By requiring confluence across 9 different analytical components before entering trades, this system significantly reduces false signals and focuses capital on only the highest-quality setups where technical, momentum, volume, and institutional factors all align. Chart showing strategy entries with confluence dashboard on 4H timeframe Why This Mashup Exists This strategy combines nine analytical frameworks that address different aspects of market analysis: CPR Analysis: Identifies key pivot levels where institutional algorithms make decisions HMA Ribbon: Measures trend quality through 5-layer moving average alignment WaveTrend Oscillator: Detects momentum cycles and overbought/oversold conditions Multi-Oscillator Divergence: Identifies momentum exhaustion across RSI, MACD, Stochastic RSI ADX Trend Strength: Quantifies trend strength to avoid weak, choppy markets Volume Confirmation: Validates moves with volume analysis and delta calculations Smart Money Concepts: Tracks institutional footprints (FVG, Order Blocks, Liquidity Sweeps) Multi-Timeframe Analysis: Ensures directional alignment across 15M, 1H, and 4H timeframes Key Moving Averages: Confirms position relative to SMA 50/200 institutional levels Each component addresses a different market dimension: CPR provides static structure, HMA shows trend quality, WaveTrend captures momentum cycles, Divergences warn of exhaustion, ADX measures trend strength, Volume confirms genuine moves, SMC reveals institutional behavior, MTF ensures alignment, and Key MAs provide institutional context. Together, they create a multi-dimensional analysis system that no single indicator can provide. The mashup is justified because these components use fundamentally different data and methodologies (pivot calculations, weighted moving averages, wave oscillators, directional movement, volume analysis, price inefficiencies, multi-timeframe data, simple moving averages) that respond to different market conditions. When they align, it indicates genuine high-probability setup rather than noise from a single analytical method. Core Strategy Logic 1. CPR Analysis Component (0-15 points) Central Pivot Range provides structural reference levels: // Daily and Weekly CPR calculation = calcCPR(dHigh, dLow, dClose) = calcCPR(wHigh, wLow, wClose) // CPR scoring cprBullScore = 0 cprBullScore += close > dPivot and close > wPivot ? 10 : 0 cprBullScore += close > dTC ? 3 : 0 cprBullScore += cprNarrow ? 2 : 0 // Narrow CPR = breakout potential cprBearScore = 0 cprBearScore += close < dPivot and close < wPivot ? 10 : 0 cprBearScore += close < dBC ? 3 : 0 cprBearScore += cprNarrow ? 2 : 0 CPR contribution: Up to 15 points for strong position relative to pivots with narrow CPR indicating breakout potential. 2. HMA Ribbon Alignment Component (0-15 points) 5-layer Hull Moving Average ribbon measures trend quality: // Calculate 5 HMAs hma8 = hullMA(close, 8) hma13 = hullMA(close, 13) hma21 = hullMA(close, 21) hma34 = hullMA(close, 34) hma55 = hullMA(close, 55) // Full alignment check hmaFullBullish = hma8 > hma13 and hma13 > hma21 and hma21 > hma34 and hma34 > hma55 hmaFullBearish = hma8 < hma13 and hma13 < hma21 and hma21 < hma34 and hma34 < hma55 // EMA cloud emaCloudBullish = emaFast > emaSlow // HMA scoring hmaRibbonBullScore = 0 hmaRibbonBullScore += hmaBullish ? 5 : 0 hmaRibbonBullScore += hmaFullBullish ? 7 : 0 // Full alignment = strong trend hmaRibbonBullScore += emaCloudBullish ? 3 : 0 HMA contribution: Up to 15 points for full ribbon alignment with EMA cloud confirmation. 3. WaveTrend Oscillator Component (0-15 points) WaveTrend detects momentum cycles and extreme conditions: = calcWaveTrend(hlc3, wtChannelLen, wtAverageLen) // WaveTrend signals wtCrossUp = ta.crossover(wt1, wt2) wtCrossDown = ta.crossunder(wt1, wt2) wtOversold = wt1 < -60 wtOverbought = wt1 > 60 // WaveTrend scoring wtBullScore = 0 wtBullScore += wtCrossUp and wtOversold ? 8 : wtCrossUp ? 5 : 0 wtBullScore += wtBullDiv ? 5 : 0 // Divergence adds weight wtBullScore += wtMomentumBullish ? 2 : 0 WaveTrend contribution: Up to 15 points for crossover in extreme zone with divergence and momentum confirmation. 4. Multi-Oscillator Divergence Component (0-10 points) Tracks divergences across RSI, MACD, and Stochastic RSI: // Divergence detection rsiBullDiv = price LL and rsi HL wtBullDiv = price LL and wt1 HL strongBullDiv = rsiBullDiv and wtBullDiv // Divergence scoring divBullScore = 0 divBullScore += rsiBullDiv ? 5 : 0 divBullScore += strongBullDiv ? 5 : 0 // Multiple oscillators = stronger signal Divergence contribution: Up to 10 points for multi-oscillator divergence indicating momentum exhaustion. 5. ADX Trend Strength Component (0-10 points) ADX quantifies trend strength to avoid choppy markets: = ta.dmi(adxLength, adxLength) strongTrend = adx > adxThreshold // Default: 20 trendBullish = plus > minus // ADX scoring adxBullScore = strongTrend and trendBullish ? 10 : trendBullish ? 5 : 0 ADX contribution: Up to 10 points for strong trend (ADX > 20) in correct direction. 6. Volume Confirmation Component (0-10 points) Volume analysis validates genuine institutional participation: volMA = ta.sma(volume, volMaLength) highVolume = volume > volMA * 1.5 climaxVolume = volume > volMA * 3.0 // Volume delta volumeDelta = ta.cum(buyVolume) - ta.cum(sellVolume) deltaRising = volumeDelta > volumeDeltaMA // Volume scoring volBullScore = 0 volBullScore += volConfirmedBull ? 7 : bullishVolume ? 5 : 0 volBullScore += climaxVolume and close > open ? 3 : 0 Volume contribution: Up to 10 points for high volume with rising delta confirming institutional buying. 7. Smart Money Concepts Component (0-10 points) SMC tracks institutional order flow patterns: // Fair Value Gaps significantBullFVG = bullishFVG and fvgSize > 0.3% // Order Blocks bullishOB = bearish candles + strong bullish candle + high volume // Liquidity Sweeps volConfirmedSweepLow = sweep below recent low + high volume // Displacement bullishDisplacement = large candle (> 2x ATR) + climax volume // SMC scoring smcBullScore = 0 smcBullScore += significantBullFVG ? 2 : 0 smcBullScore += bullishOB ? 2 : 0 smcBullScore += volConfirmedSweepLow ? 2 : 0 smcBullScore += bullishDisplacement ? 3 : 0 SMC contribution: Up to 10 points for multiple institutional footprints (FVG + OB + Sweep + Displacement). 8. Multi-Timeframe Analysis Component (0-15 points) Ensures directional alignment across higher timeframes: // Request higher timeframe data = request.security(syminfo.tickerid, "15", htfTrend()) = request.security(syminfo.tickerid, "60", htfTrend()) = request.security(syminfo.tickerid, "240", htfTrend()) // Alignment check mtfBullish = htf15mDir == 1 and htf1hDir == 1 and htf4hDir == 1 mtfStrongBullish = mtfBullish and htf15mStrong and htf1hStrong and htf4hStrong // MTF scoring mtfBullScore = 0 mtfBullScore += mtfStrongBullish ? 15 : mtfBullish ? 10 : htf1hDir == 1 ? 5 : 0 MTF contribution: Up to 15 points for all three higher timeframes aligned with strong trends. 9. Key Moving Average Component (0-10 points) Position relative to institutional moving averages: sma50 = ta.sma(close, 50) sma200 = ta.sma(close, 200) goldenCross = sma50 > sma200 // MA scoring maBullScore = 0 maBullScore += close > sma50 ? 3 : 0 maBullScore += close > sma200 ? 4 : 0 maBullScore += goldenCross ? 3 : 0 MA contribution: Up to 10 points for price above key MAs with Golden Cross. Dashboard showing confluence score breakdown by component Total Confluence Scoring System The strategy calculates total confluence score (0-100) by summing all components: bullConfluenceScore = cprBullScore + // 0-15 hmaRibbonBullScore + // 0-15 wtBullScore + // 0-15 divBullScore + // 0-10 adxBullScore + // 0-10 volBullScore + // 0-10 smcBullScore + // 0-10 mtfBullScore + // 0-15 maBullScore // 0-10 // Total: 0-100 Entry signals require: Bullish confluence score >= minConfluenceScore (default: 70) Bearish confluence score < 30 (avoid conflicting signals) Optional session filter (London/NY sessions only) Signal tiers: LONG: Confluence score >= 70 STRONG LONG: Confluence score >= 80 ULTRA LONG: Confluence score >= 90 (rare, highest probability) Risk Management System The strategy implements comprehensive risk controls: 1. ATR-Based Position Sizing atr = ta.atr(14) stopLossDistance = atr * 2 // Calculate position size based on risk accountSize = strategy.equity riskAmount = accountSize * (riskPercent / 100) // Default: 2% positionSize = riskAmount / stopLossDistance 2. Dynamic Stop Loss and Take Profit // Dynamic stop based on market structure dynamicStopBull = math.min(close - stopLossDistance, ta.lowest(low, 10)) // Take profit based on risk:reward ratio takeProfit = close + (stopLossDistance * rewardRatio) // Default: 2:1 3. Breakeven Management // Move stop to breakeven when profit reaches threshold if close >= entryPrice + (stopLossDistance * breakevenTrigger) // Default: 1.0 R:R strategy.exit("Long Exit", "Long", stop=entryPrice, limit=takeProfit) 4. Trailing Stop (Optional) if useTrailingStop trailDistance = close * (trailOffset / 100) // Default: 1.5% strategy.exit("Long Exit", "Long", trail_offset=trailDistance) Strategy Execution Logic // Long Entry if longSignal and strategy.position_size == 0 stopLoss = dynamicStopBull takeProfit = close + (stopLossDistance * rewardRatio) strategy.entry("Long", strategy.long) strategy.exit("Long Exit", "Long", stop=stopLoss, limit=takeProfit) // Label with confluence score label.new(bar_index, low, "LONG Score: " + str.tostring(bullConfluenceScore), style=label.style_label_up, color=entryColor) // Short Entry (mirror logic) if shortSignal and strategy.position_size == 0 // Similar logic for short trades Performance Dashboard The strategy displays a comprehensive 12-row dashboard: Row 1: Component header Row 2: Current position (LONG/SHORT/FLAT) Row 3: Total confluence score (bull/bear) Row 4: CPR component score Row 5: HMA Ribbon component score Row 6: WaveTrend component score Row 7: Divergence component score Row 8: ADX component score Row 9: Volume component score Row 10: SMC component score Row 11: MTF component score Row 12: Equity and P&L percentage Strategy Parameters Strategy Settings: Use Multi-Timeframe Confirmation: Enable MTF analysis (default: enabled) Use Divergence Signals: Enable divergence component (default: enabled) Use Smart Money Concepts: Enable SMC component (default: enabled) Use Volume Confirmation: Enable volume component (default: enabled) Use CPR Levels: Enable CPR component (default: enabled) Use WaveTrend Signals: Enable WaveTrend component (default: enabled) Use HMA Alignment: Enable HMA component (default: enabled) Use Session Filter: Trade only during London/NY sessions (default: enabled) Minimum Confluence Score: Threshold for entry (default: 70, range: 50-100) Risk Management: Risk Per Trade %: Percentage of equity to risk (default: 2.0%, range: 0.1-10%) Reward:Risk Ratio: Take profit multiplier (default: 2.0, range: 1.0-5.0) Use Trailing Stop: Enable trailing stop (default: enabled) Trailing Stop %: Trail distance (default: 1.5%, range: 0.1-5.0%) Use Breakeven: Move stop to breakeven (default: enabled) Breakeven Trigger: R:R threshold to move stop (default: 1.0, range: 0.5-3.0) Indicator Parameters: RSI Length: Period for RSI (default: 14) ADX Length: Period for ADX (default: 14) ADX Threshold: Minimum ADX for strong trend (default: 20) Volume MA Length: Period for volume average (default: 20) HMA Length: Period for HMA (default: 21) WaveTrend Channel Length: (default: 10) WaveTrend Average Length: (default: 21) Backtesting Configuration Default strategy properties: Initial Capital: $10,000 Default Qty Type: Percent of Equity Default Qty Value: 10% Commission Type: Percent Commission Value: 0.1% (10 basis points) Slippage: 2 ticks Max Bars Back: 5000 These settings represent realistic trading conditions for the average trader. Commission and slippage account for typical broker fees and execution costs. How to Use This Strategy Step 1: Configure Components Enable/disable components based on your trading style. All components enabled provides maximum filtering but fewer trades. Step 2: Set Confluence Threshold Adjust minimum confluence score. Higher threshold (80-90) = fewer, higher-quality trades. Lower threshold (60-70) = more frequent trades. Step 3: Configure Risk Parameters Set risk per trade (1-2% recommended) and reward:risk ratio (2:1 minimum recommended). Enable breakeven and trailing stop for protection. Step 4: Backtest Thoroughly Run backtests on multiple timeframes and market conditions. Aim for 100+ trades for statistical significance. Review win rate, profit factor, and drawdown. Step 5: Analyze Component Contribution Use dashboard to see which components contribute most to winning trades. Consider adjusting weights or disabling low-value components. Step 6: Forward Test Paper trade the strategy before risking real capital. Verify that live results align with backtest expectations. Best Practices Use on 15-minute to 4-hour timeframes for optimal signal quality Confluence score above 80 produces highest win rate but fewer trades Enable all components for maximum filtering in volatile markets Disable some components for more frequent trades in trending markets Session filter (London/NY only) significantly improves results Risk 1-2% per trade maximum for sustainable trading Aim for minimum 2:1 reward:risk ratio Review dashboard component scores to understand trade quality Backtest on minimum 6-12 months of data Verify 100+ trades in backtest for statistical validity Strategy Limitations Confluence-based systems produce fewer trades - may not suit active traders Requires all components to align - perfect setups are rare Backtesting results may not reflect live trading with slippage and latency Multi-timeframe analysis can cause repainting on lower timeframes High confluence threshold (90+) may produce too few trades for some markets Commission and slippage significantly impact profitability Strategy optimized for trending markets - may underperform in ranges Past performance does not guarantee future results Requires understanding of all components for effective parameter tuning Complex system with many parameters - over-optimization risk Backtesting Considerations When evaluating backtest results: Sample Size: Minimum 100 trades for statistical significance Win Rate: 40-60% is realistic for 2:1 R:R strategy Profit Factor: Above 1.5 is good, above 2.0 is excellent Max Drawdown: Should be less than 20% of initial capital Sharpe Ratio: Above 1.0 indicates good risk-adjusted returns Trade Frequency: Should match your trading availability Equity Curve: Should show steady growth, not erratic spikes Consecutive Losses: Prepare for 5-10 consecutive losses Adjust parameters if: Win rate < 35% with 2:1 R:R (increase confluence threshold) Too few trades (< 50 in 6 months) (decrease confluence threshold or disable some components) Max drawdown > 25% (reduce risk per trade or increase confluence threshold) Profit factor < 1.2 (strategy may not be viable) Technical Implementation Built with Pine Script v6 using: 9-component confluence scoring system CPR calculations with width analysis 5-layer HMA ribbon with full alignment detection WaveTrend oscillator with divergence tracking Multi-oscillator divergence detection (RSI, MACD, Stoch RSI) ADX trend strength measurement Volume analysis with delta calculations Smart Money Concepts (FVG, OB, Liquidity Sweeps, Displacement) Multi-timeframe analysis (15M, 1H, 4H) ATR-based dynamic position sizing Breakeven and trailing stop management Comprehensive 12-row dashboard Session filtering (London/NY) The code is fully open-source and can be modified to adjust component weights, confluence thresholds, and risk parameters. Originality Statement This strategy is original in its comprehensive multi-component confluence approach. While individual components (CPR, HMA, WaveTrend, Divergences, ADX, Volume, SMC, MTF, Key MAs) are established analytical tools, this mashup is justified because: It integrates 9 independent analytical frameworks using fundamentally different data and methodologies The confluence scoring system quantifies setup quality across all components (0-100 scale) Each component addresses a different market dimension (structure, trend, momentum, strength, volume, institutional flow, timeframe alignment) Tiered signal system (LONG/STRONG/ULTRA) provides graduated confidence levels Comprehensive risk management with ATR-based sizing, breakeven, and trailing stops Component-level dashboard allows traders to understand what drives each trade Session filtering aligns with institutional trading hours Integration reveals complete market picture that no single indicator provides Each component contributes unique information: CPR provides structure, HMA shows trend quality, WaveTrend captures momentum cycles, Divergences warn of exhaustion, ADX measures strength, Volume confirms moves, SMC reveals institutional behavior, MTF ensures alignment, and Key MAs provide institutional context. The strategy's value lies in requiring confluence across these independent frameworks, significantly reducing false signals and focusing capital on only the highest-probability setups where all factors align. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Backtesting results do not guarantee future performance. Past results, whether real or indicated by historical tests, are not indicative of future results. There are frequently sharp differences between backtested results and actual results subsequently achieved by any trading strategy. The confluence score is a mathematical calculation based on current market data, not a prediction of future price movement. High confluence scores do not ensure profitable trades. Market conditions change, and strategies that worked historically may not work in the future. Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, broker fees, and other factors not captured in backtesting. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown in backtests. Users should thoroughly test any strategy in a paper trading environment before risking real capital. Always use proper risk management. Never risk more than you can afford to lose. The default 2% risk per trade is a guideline - adjust based on your personal risk tolerance and account size. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this strategy. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades
กลยุทธ์ Pine Script®
โดย officialjackofalltrades
3
Mean Reversion V-F V.1I received lot of request to publish better version of Mean Reversion V-F so here you go In V.1 WE going in Long trade after MA falling # of bars The # of bars can be adjust from the settings New calculation for deviations - after the first trade calculation start from close of the bar and so on The first trade is market trade the rest are limit trades so can get to it in any time if the price drop to that deviations level Can be use for crypto and stocks For stocks just enable Use for Stocks and input # of stocks The strategy gave my lot better results and less drown down If any question let my know Happy trading
กลยุทธ์ Pine Script®
โดย fullmax
SuperTrend AI Adaptive - Strategy [BTC]+2,091% returns. 1.94 profit factor. 28% max drawdown. Buy and hold returned ~785% over the same period with 75%+ drawdowns. This strategy returned 2,091% with less than a third of the drawdown. Consistent upward equity curve through bull markets, bear markets, and sideways chop. This is the strategy version of SuperTrend AI . Same regime-adaptive engine, same AI scoring, now with full entries, exits, and risk management built in. ◈ How It Works The strategy detects market regime shifts (trending, volatile, ranging) and adapts the SuperTrend multiplier automatically. Every trend flip is scored 0-100 by a 5-factor AI engine. Only high-scoring flips become trade entries. The 5 scoring factors: Volume Surge: was there conviction behind the flip? Displacement: how far did price break through the band? Trend Alignment: does the EMA agree with the direction? Regime Quality: trending regimes score highest, ranging get penalized Band Distance: how far did price travel to reach the flip point? Low-scoring flips are skipped entirely. This is the main edge. Standard SuperTrend enters on every flip. This strategy is selective. ◈ Regime Adaptation TRENDING regime: multiplier stays at base. Normal conditions, normal entries. VOLATILE regime: multiplier widens automatically. Prevents noise-driven entries. Band turns amber on chart. RANGING regime: multiplier tightens slightly. Entries are blocked by default because SuperTrend gets chopped in ranges. The regime filter alone eliminates most of the losing trades that kill standard SuperTrend strategies. ◈ Risk Management Three stop loss modes: ATR-based (default): dynamic stop that adjusts to current volatility Percent: fixed percentage stop SuperTrend: exit only on trend flip Take profit modes: Risk:Reward ratio (default 2.5:1): TP based on SL distance Percent: fixed percentage target None: hold until stop or flip Optional trailing stop for locking in profits on extended trends. All parameters are adjustable. ◈ Why It Beats Buy and Hold Buy and hold works in hindsight. In real time, you sit through 50-75% drawdowns hoping for recovery. This strategy: Shorts during bear markets instead of bleeding. The 2022 and early 2026 bear legs were profitable, not just survivable. Stays flat during ranging markets. No entries when conditions are bad. Compounds gains from both directions. Longs in uptrends, shorts in downtrends. The equity curve tells the story. Consistent staircase up with controlled pullbacks vs the rollercoaster of buy and hold. ◈ Default Settings (optimized for BTCUSDT 4H) SuperTrend: ATR 10, Base Multiplier 3.0 Regime: Lookback 40, ADX 14, Threshold 20 AI Engine: Trend EMA 50, Volume MA 20, Min Score 65 Risk: SL Mode ATR, SL ATR Mult 6.0, TP Mode RR 2.5:1 Filters: EMA Trend Filter on, Skip Ranging on, Volume Filter on, Cooldown 5 Position: 80% of equity per trade Commission: 0.06% (Binance futures level), 2 ticks slippage ◈ Adapting to Other Assets These defaults are tuned for BTCUSDT 4H. For other assets, adjust: Other crypto (ETH, SOL) 4H: Same settings, may need Min Score 60 Forex 1H to 4H: Lower position size to 20-30%, tighten SL to 2.5-3.0 ATR, trend following works less well on forex Indices 1H: SL ATR 3.0-4.0, position size 30-50% SuperTrend strategies work best on assets that trend. Crypto on higher timeframes trends the hardest. ◈ Backtest Notes Period: Jan 2015 to Feb 2026 (10+ years, includes multiple bull and bear cycles) Initial capital: $10,000 USDT Commission: 0.06% per trade (realistic for Binance futures) Slippage: 2 ticks Position sizing: 80% of equity (compounding) No pyramiding. One position at a time. Signals are non-repainting. Entries on confirmed bar close only. Returns are compounded. The 2,091% figure reflects reinvesting profits at 80% equity per trade. Without compounding, the raw edge is captured by the profit factor (1.94) and win rate (46% at 2.5:1 RR). ◈ Key Metrics Total P&L: +2,091% Profit Factor: 1.94 Win Rate: 46.10% (71 of 154 trades) Max Drawdown: 28.16% Average trade count: roughly 15 per year ◈ Features ✓ Regime-adaptive SuperTrend with automatic multiplier adjustment ✓ AI signal scoring filters out low-quality trend flips ✓ Three SL modes (ATR, Percent, SuperTrend flip) ✓ Three TP modes (Risk:Reward, Percent, None) ✓ Optional trailing stop ✓ EMA trend filter, regime filter, volume filter ✓ Realistic commission and slippage included ✓ Dashboard showing trend, regime, position status, and signal score ✓ Non-repainting entries on confirmed bar close ✓ 100% original code ◈ Companion Indicator This strategy is built on the SuperTrend AI indicator. Use the indicator for live chart analysis and the strategy for backtesting and validation. Both available free on my profile. ◈ Disclaimer Past backtest performance does not guarantee future results. All backtests have inherent limitations including look-ahead bias in parameter selection. These settings were optimized on the full sample period. Always forward-test before risking real capital. Use proper position sizing and risk management. This is not financial advice. Happy trading.
กลยุทธ์ Pine Script®
โดย DefinedEdge
4
Block-Based Visual Logic Builder FrameworkThis strategy demonstrates a modular, block-based approach to strategy design in Pine Script. While TradingView does not support true drag-and-drop strategy builders, this script is structured to simulate a visual logic builder by separating trading logic into independent, configurable blocks. Each block represents a conceptual component (trend, momentum, volatility, session, and risk), allowing users to enable, disable, or modify individual modules for testing and experimentation. Visual Logic Builder Concept The strategy is organized into distinct logic blocks: Session Block - controls when trades are allowed Trend Block - defines directional bias Momentum Block - confirms directional strength Volatility Block - filters for sufficient market movement Risk Block - standardized ATR-based stop and target logic This structure mirrors how visual trading systems and drag-and-drop interfaces organize logic into reusable components. How It Works Market conditions are evaluated through separate logic blocks. Each block can be enabled or disabled using inputs. Final entry decisions are based on the combined output of active blocks. All exits are managed through a centralized risk block using ATR-based stops and fixed risk-reward. Purpose This script is intended as a structural template for building and testing modular trading systems. It emphasizes clarity, execution realism, and repeatable logic rather than optimization or signal density. Usage Notes Results depend on symbol, timeframe, volatility regime, and selected block settings. Users are encouraged to experiment with different combinations of blocks and validate behavior across multiple markets before relying on any configuration.
กลยุทธ์ Pine Script®
โดย AIScripts
Modular Trend Pullback StrategyThis strategy focuses on trading pullbacks within established trends. Instead of entering immediately when a trend forms, it waits for a temporary retracement and then looks for confirmation before placing a trade. The goal is to improve entry timing while keeping risk controlled. Core Idea Markets often move in waves. During a strong trend, price tends to retrace toward a short-term average before continuing in the dominant direction. This script attempts to participate in those continuation moves. How It Works 1. Trend Identification Two exponential moving averages (EMAs) define direction. Fast EMA above Slow EMA → bullish environment Fast EMA below Slow EMA → bearish environment 2. Pullback Condition In an uptrend, price must retrace below the fast EMA. In a downtrend, price must retrace above the fast EMA. This avoids chasing extended moves. 3. Break Confirmation After a pullback, the strategy waits for price to break the previous candle’s high (for longs) or low (for shorts). This acts as confirmation that momentum is returning in the direction of the trend. 4. Risk Management Stop-loss and take-profit levels are based on ATR (Average True Range), allowing exits to adapt to current volatility. A configurable risk-reward ratio defines profit targets. Key Features Non-repainting logic Entries only when flat (no stacking positions) ATR-based dynamic stop and target levels Commission and slippage included for more realistic backtests Structured, modular logic for easier testing and adjustment Suitable Market Conditions This type of approach generally performs best in: Trending environments Instruments with sustained directional movement Timeframes where pullbacks are clearly visible It may underperform in sideways or low-volatility markets. Notes This script is intended for research and testing purposes. Results will vary depending on symbol, timeframe, and market regime. Always evaluate performance across multiple market conditions before considering live execution.
กลยุทธ์ Pine Script®
โดย AIScripts
Structural Volatility Expansion StrategyStructural Volatility Expansion Strategy Purpose This strategy studies the relationship between confirmed market structure breaks and volatility regime shifts. Its objective is to participate in directional expansions that occur after structural confirmation, while filtering out low-volatility consolidations and false breakouts. The script is intended for research and systematic evaluation, not predictive claims. Methodology The model combines three interacting components: 1. Confirmed Structural Break Logic Market structure is derived using confirmed pivot highs and pivot lows. A bullish structural break is defined as a close above the most recent confirmed pivot high. A bearish structural break is defined as a close below the most recent confirmed pivot low. Pivots require full bar confirmation, which prevents forward-looking bias and repainting. This approach differs from simple rolling highest/lowest calculations by using structurally validated turning points. 2. Volatility Regime Classification Volatility is measured using ATR relative to its moving average baseline. Two regimes are defined: Compression: ATR below its historical baseline. Expansion: ATR above its historical baseline. Trades are only allowed during expansion phases. This attempts to reduce participation during statistically lower-momentum environments. 3. Liquidity Sweep Filter Breakouts that wick beyond structural levels but fail to close beyond them are treated as liquidity sweeps and are excluded. This reduces exposure to stop-run reversals where structure appears broken intrabar but fails on close. 4. Higher Timeframe Alignment Directional bias is determined using a higher timeframe moving average. Long entries require higher timeframe close above its MA. Short entries require higher timeframe close below its MA. Lookahead is disabled to avoid repainting. This introduces multi-timeframe confirmation without using future data. Risk Management Default strategy properties: Initial capital: 10,000 Position sizing: 2% of equity per trade Commission: 0.04% Slippage: 2 ticks Pyramiding: Disabled Stops are ATR-based and targets use a fixed risk-reward multiple (default 2:1). The position sizing is intentionally conservative and does not exceed commonly accepted sustainable risk thresholds. Backtesting Transparency When evaluating results: Use markets with sufficient liquidity. Ensure a dataset that generates a meaningful number of trades (ideally 100+). Keep default commission and slippage settings unchanged. Avoid optimizing inputs solely to maximize historical performance. Performance results are dependent on instrument, timeframe, and historical period tested. This script does not guarantee profitability and should be forward-tested before any live use. Intended Use This strategy is designed for: Studying structural continuation patterns Researching volatility regime transitions Comparing breakout performance during expansion vs compression Systematic strategy development It is not intended as financial advice. Originality Notes The script: Uses confirmed pivot-based structure rather than raw lookback highs/lows Filters entries by volatility regime classification Excludes wick-only structural violations Applies non-repainting higher timeframe bias Uses realistic transaction cost modeling The logic emphasizes interaction between structure and volatility rather than indicator stacking. Limitations & Responsible Use This strategy has several important limitations: Lag From Pivot Confirmation Structural pivots require confirmation, which introduces delay. Signals may occur after a portion of the move has already developed. ATR Sensitivity Volatility classification depends on ATR relative to its baseline. During regime transitions, expansion signals may appear slightly late or briefly revert to compression. Trend Dependency The strategy performs best during directional market phases. Extended sideways environments may reduce performance even with volatility filtering. Higher Timeframe Influence The higher timeframe moving average is a smoothing mechanism and may not capture sudden macro shifts immediately. Market Specific Behavior Different asset classes (crypto, forex, equities, indices) exhibit different volatility cycles. Parameters may require testing across multiple datasets rather than optimization for a single instrument. Backtest Limitations Historical testing does not account for: Liquidity variations Execution delays Psychological decision-making factors Structural market changes over time Forward testing and risk control are recommended before any real capital deployment. Suggested Evaluation Approach For objective evaluation: Test across multiple years of data. Use instruments with consistent liquidity. Maintain realistic commission and slippage settings. Avoid curve-fitting inputs to a specific historical window. Compare results across trending and ranging environments. Risk Disclaimer This script is provided for research and educational purposes only. It does not constitute investment advice. All trading involves risk, and past performance does not guarantee future results.
กลยุทธ์ Pine Script®
โดย JaxonJackFX
VWAP Reversal Strategy V1🔹 VWAP Reversal Strategy V1 by COT-Trader.com The VWAP Reversal Strategy V1 is a selective intraday framework designed to capture structured pullbacks to VWAP after a confirmed breakout. It focuses on quality over frequency and integrates volatility, confirmation and optional higher timeframe bias filtering. This strategy is part of the systematic trading research published at 👉 cot-trader.com 📌 Core Concept Markets frequently break above or below VWAP (fair value), only to retest it before continuation. This strategy trades that sequence: Long Setup Price breaks above VWAP A retest of VWAP occurs within a defined number of bars A bullish confirmation candle forms Optional filters align Entry at confirmation Short Setup Mirrored logic below VWAP (can be disabled). 📊 Built-In Filters To increase selectivity, the following filters can be enabled: • Rejection wick confirmation • Volume spike confirmation • Minimum ATR-based distance from VWAP • Optional H1 VWAP directional bias All filters are configurable. ⚙ Risk Management The strategy uses: • ATR-based Stop Loss • ATR-based Take Profit • Maximum trades per day limit • Optional session filter The goal is consistency and controlled exposure rather than high trade frequency. 🧠 Intended Use Designed for intraday timeframes (typically 15–30 minutes). Works best in structured, liquid markets. Extensive debug markers can be enabled for research purposes. ⚠ Disclaimer This script is published for educational and research purposes only. It does not constitute financial advice. Always test strategies in simulation before using real capital.
กลยุทธ์ Pine Script®
โดย DerAndi72
2
XAUUSD Breakout Retest Sniper StrategyThis strategy is designed to demonstrate a structured breakout + retest approach using trend confirmation and volatility-based risk management. It is built for educational and research purposes to help traders understand how breakout continuation moves can be analyzed systematically. The logic focuses on identifying key breakout zones from recent highs and lows, then waiting for price confirmation in the direction of the prevailing trend before simulating entries. Core Logic Behind the Strategy Uses a trend filter (EMA) to define directional bias Identifies recent resistance and support using lookback highs/lows Waits for breakout confirmation and retest behavior Applies ATR-based stop loss and risk-to-reward target projection Designed for intraday charts such as 5M–15M (can be adjusted) The strategy aims to model how price often moves from one liquidity zone to another after breaking key levels. It avoids trading in consolidation and focuses only on confirmed directional moves. How It Works • Bullish conditions when price is above trend EMA • Bearish conditions when price is below trend EMA • Breakout of recent structure signals potential continuation • ATR used to simulate dynamic SL and TP levels • Built-in backtesting for study and optimization Important Notes This script is a technical model for chart study and strategy development. It does not guarantee performance and should not be used as financial advice or a signal service. Users are encouraged to test, modify, and adapt it according to their own trading plans and risk management rules. Best Use Learning breakout + retest behavior Backtesting structured entry models Studying trend-based continuation setups Developing personal trading systems Disclaimer This publication is for educational and informational purposes only. Trading involves risk, and past performance does not guarantee future results. Always perform your own analysis before making trading decisions. xauusd, gold, strategy, breakout, price action, algorithmic trading, trend trading
กลยุทธ์ Pine Script®
โดย JaxonJackFX
Grid Bot Demonstrator🚀 Grid Bot Demonstrator Overview The Grid Bot Demonstrator is a high-performance visualization tool designed for traders utilizing Grid Trading strategies (similar to Pionex, Binance, or KuCoin). It allows you to simulate and visualize a grid bot's structure directly on your chart, enabling precise planning of ranges and grid density before deploying capital. 🛠 Key Features Dynamic Auto-Range: When limits are set to 0, the indicator automatically calculates an optimal range (±10% from current price) rounded to the nearest $10,000—ideal for Bitcoin’s psychological levels. Dual Mode Support: Seamlessly toggle between Long and Short strategies via a simple dropdown menu. Intelligent Grid Coloring: Long Mode: Green lines above price (Take Profit), Red lines below (Buy/Support). Short Mode: Red lines above price (Entry/Stop), Green lines below (Take Profit). Performance Optimized (Smart Window): Even with up to 500 grids , the chart remains fluid. The script renders only the 100 lines closest to the current price while maintaining perfect mathematical accuracy of the total grid count. Boundary Protection: Features bold, distinct safety lines for the Upper and Lower limits so you know exactly when your bot leaves the active trading zone. 📖 How to Use 1. Grid Settings Enter your Upper and Lower price limits. Use "0" for the automated 10k-rounding logic. 2. Grid Count Set the number of grids (up to 500) to match your bot's specific configuration. 3. Strategy Mode Select "Long" or "Short" to instantly adapt the color coding to your trade direction. 4. Scalability Works across all timeframes, from 1-minute scalping to daily charts. 🔬 Technical Specifications Grid Type: Arithmetic (Equal USD distance between levels). Engine: Pine Script V5 with max_lines_count optimization. Clarity: Focuses on visual price levels to provide a clean, distraction-free trading environment.
อินดิเคเตอร์ Pine Script®
โดย AlexTrading2022
Game Theory Strategic Indicator - Archery & Horse Riding Model# Game Theory Strategic Indicator - Archery & Horse Riding Model ## Overview This indicator applies rigorous game theory mathematics to market analysis, modeling price action as a strategic two-player game between buyers and sellers. The methodology draws from economic game theory, evolutionary dynamics, and zero-sum game optimization. ## Theoretical Foundation The indicator implements five core game theory concepts: **1. Expected Utility (Mixed Strategies)** Calculates E = p×U₁ + (1-p)×U₂ where: - p = probability distribution based on volume dynamics - U₁, U₂ = utility payoffs for aggressive vs defensive strategies - Uses RSI momentum and ATR volatility to quantify payoffs **2. Nash Equilibrium Detection** Identifies market states where ui(σᵢ*, σ₋ᵢ*) ≥ ui(σᵢ, σ₋ᵢ*): - Measures when no participant can improve by changing strategy - Highlighted with yellow background zones - Signals reduced edge environments (avoid trading) **3. Replicator Dynamics** Models evolutionary strategy adaptation: dx/dt = x(f(x) - φ(x)) - Tracks frequency changes in bullish vs bearish strategies - Shows which approach is gaining evolutionary fitness - Purple line indicates strategy evolution trend **4. Minimax Algorithm** Implements zero-sum game optimal strategy L(x,y): - Calculates win/loss ratio over lookback period - Values > 1.0 suggest favorable risk/reward - Orange line shows deviation from neutral state **5. Best Response Function** Determines optimal action maximizing ui(aᵢ, a₋ᵢ): - Compares buyer vs seller expected utilities - Generates primary long/short signals - Confidence weighted by utility differential ## Visual Elements **Chart Plots:** - **Blue Line (Utility Differential)**: Buyer utility minus seller utility. Positive favors longs, negative favors shorts - **Purple Line (Replicator Dynamics)**: Rate of strategy evolution. Rising = bullish strategies gaining fitness - **Orange Line (Minimax Deviation)**: Zero-sum game value. Above zero = favorable conditions - **Pink Area (Mixed Strategy Bias)**: Probability-weighted strategy preference - **Yellow Background**: Nash equilibrium zones where no player has edge **Signals:** - **Green Triangle Up**: Long signal - buyer utility dominates outside equilibrium - **Red Triangle Down**: Short signal - seller utility dominates outside equilibrium - **Yellow Diamond**: Equilibrium warning - reduced edge state **Info Table (Top Right):** - EU Buyer/Seller: Current expected utilities - Nash Score: Equilibrium strength (>0.65 = equilibrium) - Mix Prob: Volume-based probability distribution - Minimax: Win/loss ratio indicator ## Strategy Metaphors **Archery (Buyer Strategy)**: Represents precision attacks - targeted entries at optimal risk/reward points, high accuracy required **Horse Riding (Seller Strategy)**: Represents mobile defense - flexible positioning, quick exits, adaptive to changing terrain ## Parameters - **Strategy Period (14)**: Lookback for RSI and ATR calculations - **Mixed Strategy Length (21)**: Period for minimax win/loss analysis - **Nash Equilibrium Threshold (0.65)**: Minimum score to identify equilibrium (0.5-0.9) - **Show Trade Signals**: Toggle buy/sell arrows - **Show Equilibrium Zones**: Toggle background highlighting ## How to Use 1. **Trend Trading**: Take long signals when utility differential (blue) is rising and no equilibrium zone present 2. **Counter-Trend**: Take signals when replicator dynamics (purple) diverges from price 3. **Risk Management**: Avoid trading during yellow equilibrium zones - market has no clear edge 4. **Confirmation**: Best signals occur when minimax > 1.0 and best response aligns with utility differential 5. **Monitoring**: Watch info table for real-time utility balance and equilibrium status ## Alerts Three alert conditions available: - **GT Long Signal**: Buyer utility dominates, composite score > 0.5 - **GT Short Signal**: Seller utility dominates, composite score < -0.5 - **Nash Equilibrium**: Market reaches balanced state, avoid new entries ## Mathematical Rigor All calculations use proper game theory formulations: - Payoff functions normalized by volatility - Probability distributions bounded - Zero-division protection implemented - Utilities properly weighted in composite score ## Originality Statement This indicator is original work implementing classical game theory mathematics in a novel market analysis framework. The code, calculations, and interpretation methodology are entirely my own creation. No external scripts were copied or modified. ## Disclaimer This indicator is for educational purposes. Game theory provides a framework for analyzing strategic interaction but does not guarantee profitable trading. Always use proper risk management, test thoroughly, and understand that past performance does not indicate future results. --- **Educational Resource**: For deeper understanding of game theory in economics, see Nash (1950) "Equilibrium Points in N-Person Games" and Maynard Smith (1982) "Evolution and the Theory of Games" ``` ---
อินดิเคเตอร์ Pine Script®
โดย uzair2join
TRADING BITE Supply Demand Marker V2.1This Indicator Automatically identifies key supply and demand candles and highlights potential reversal zones. Integrated volume analysis validates market moves, helping traders make more informed entry and exit decisions. Perfect for spotting high-probability trades and understanding market structure at a glance. Features: Highlights Supply & Demand zones automatically Marks key reversal candles Volume-based validation for stronger signals Easy-to-read visual alerts for trading decisions Disclaimer / No Liability Notice: This indicator is provided for educational and informational purposes only. It does not guarantee profits or predict future market movements. Trading financial instruments involves substantial risk of loss, and you should only trade with money you can afford to lose. By using this indicator, you acknowledge that you assume full responsibility for any trading decisions made based on its signals. The developer accepts no liability for any losses, damages, or financial consequences that may result from using this tool. Always perform your own analysis and consider consulting a licensed financial advisor before making trading decisions. Past performance is not indicative of future results.
อินดิเคเตอร์ Pine Script®
โดย Trading_bite
March-May Oct-Dec bank stocks strategyIn the Indian market, banking stocks have some sort of cyclic nature. If you buy at the start of March and sell at the start of May and then buy at the start of Oct and sell at the start of December, you can make gains close to to "buy and hold", while being invested only for 4 months out of 12. This seems to backtest well for post 2021 on all Bank stocks I tested, including BANKNIFTY as well Caveat: Not calculating STCG and other expenses caused by selling and buying 2 times every year.
กลยุทธ์ Pine Script®
โดย rep_movsd
1
Martingale Grid BotMartingale Grid Bot (MGB) The strategy is designed to test grid trading with a possible increase in the size of each subsequent order based on the martingale principle. The strategy itself does not contain any trade decision logic and is fully driven by external signals coming from indicators used on the chart. A new grid of orders is created when an entry signal is received, provided that there is no active grid. ❗ Warning Trading with leverage and martingale involves increased risk. This strategy is a rather rough tool and is intended for testing purposes only. The author is not responsible for any possible discrepancies between the strategy results and real trading. Settings Direction - Trading direction. Possible values: Long and Short. Entry Signal Source - Source of the entry signal that initiates the creation of a new order grid. If one of the price sources (open, high, low, close, etc.) is selected, a new grid will be created automatically after the previous grid is fully closed. Start Time - Date and time when the strategy starts operating. Marked on the chart with a vertical dashed line. No Repainting Mode - A mode intended to reduce discrepancies between historical and real-time strategy behavior (repainting). Enabled — a new grid is created only after the bar is closed. The first order can be filled no earlier than on the next bar. Disabled — in real-time, a new grid can be created immediately upon receiving a signal or after the previous grid is closed by take profit or stop loss. ❗ Attention For correct real-time operation, recalculation on every tick must be enabled in the strategy settings. GRID Grid Depth % - The depth of the order grid, specified as a percentage of the closing price at the moment the grid is created. Orders Count - The number of orders in the grid. The first order is placed at the current closing price at the time of grid creation. Martingale Multiplier - Position size multiplier. Each subsequent order in the grid will be increased by this factor. The size of the first order is defined in the strategy settings. Leverage - Leverage multiplier for margin trading. Used to check available funds when creating grid orders. It is recommended to use it together with the margin parameters in the strategy settings. Take Profit % - Calculated on each strategy update based on the average entry price. If none of the grid orders have been filled yet, the take-profit level for the first order is displayed on the chart. Stop Loss % - Calculated from the price of the first grid order and does not change during the strategy operation. Orders whose price exceeds the stop-loss level will be automatically canceled. TABLE Show Table - Controls the display of the table with all orders of the current grid. If there is no active grid, no order data is displayed. Text and background colors are determined automatically based on the chart background color. Order Size - Determines how the grid order size is displayed: in contracts or in currency. Table Size - Font size in the table. Timezone - Used to correctly display the order fill time relative to the chart time. The order fill time (status: filled) can be seen by hovering over the corresponding status cell in the table. VISUAL Long Entry - Color of the dotted lines representing grid orders when trading long. Also defines the color of the vertical line indicating the strategy start time. Short Entry - Color of the dotted lines representing grid orders when trading short. Also defines the color of the vertical line indicating the strategy start time. Take Profit - Color of the solid line representing the take-profit level. Stop Loss - Color of the solid line representing the stop-loss level.
กลยุทธ์ Pine Script®
โดย Pechka_Rider
High Breakout PRO - Huy Hoang Trader # High Breakout PRO - Huy Hoang Trader - Strategy Description ## 🚀 Overview **High Breakout PRO** is a professional-grade Trend Following strategy designed to capture major market moves while strictly managing risk. Built on the core philosophy of "Price Action Breakouts," this script enhances the classic Donchian Channel breakout method with modern risk management tools like the **Hybrid Exit** and **EMA Trend Filter**. This strategy is optimized for **Gold (XAUUSD)**, **Bitcoin (BTC)**, and **Major Stocks (AAPL, AMZN)** on **H4 and Daily** timeframes. ## 💎 Key Features 1. **Trend Filter (EMA):** Only takes long positions when the price is above the 200-period EMA. This filters out counter-trend noise and significantly improves winning probability. 2. **Hybrid Exit Mechanism ("Holy Grail"):** A unique dynamic trailing stop that combines: * **Price Structure:** Uses the lowest low of the last Y bars (Donchian Support). * **Volatility:** Uses ATR-based trailing (Chandelier Exit logic). * *Logic:* The system automatically chooses the **tighter** (higher) stop level between the two, ensuring you lock in profits rapidly during strong volatility while giving the trade room to breathe during accumulation. 3. **Professional Visuals:** A refined "Wealth & Earth" themes (Gold/Silver/Brown) specifically designed to reduce eye strain and provide clear, professional signal visibility without chart clutter. ## 🛠 Strategy Logic ### entry rules * **Breakout:** Price closes above the Highest High of the last `X` bars (Default: 20). * **Trend Confirmation:** Closing Price > EMA 200 (Configurable). ### Exit Rules * **Dynamic Stop Loss:** The trade is closed when price breaches the **Hybrid Trailing Stop**. * The Trailing Stop never moves down. It only moves up as price increases. * It effectively adapts to both slow-grinding trends and explosive spikes. ## ⚙️ Best Settings (Recommended) * **Timeframe:** H4 (Swing Trading) or Daily (Position Trading). * **Entry Period (X):** 20 * **Exit Period (Y):** 10 * **Trend Filter:** ON (EMA 200) * **Risk Management:** Hybrid Mode (ATR Multiplier 3.0) ## ⚠️ Disclaimer This strategy follows trends. It may experience drawdowns during choppy/sideways markets. Always use proper risk management (position sizing) and backtest on your specific asset before live trading. --- *Developed by Antigravity. Empowering traders with institutional-grade tools.* Contact for work: www.facebook.com
กลยุทธ์ Pine Script®
โดย ngohuyhoanghcm
SPY Quant ML + Session Filter Strategy [CocoChoco]S&P 500 Quant: Machine Learning & Mean Reversion (Session-Filtered) Overview This is a professional-grade quantitative strategy designed specifically for the S&P 500. It combines classical statistical mean reversion (Z-Score) with a modern Machine Learning filter and rigorous institutional-grade risk management. The strategy is optimized for traders who prioritize high win rates and capital preservation, specifically avoiding the "gap risk" associated with holding positions overnight. Core Methodology 1. Statistical Entry (The Z-Score Engine) The strategy identifies "oversold" conditions in a bullish context. It calculates the Z-Score of the price relative to its 20-period Mean (SMA). By default, it looks for a -1.2 Standard Deviation extension, signaling a high-probability "dip" ripe for a snap-back to the mean. 2. Trend & ML Filters To avoid "catching a falling knife," the strategy uses two layers of confirmation: Trend Filter: Only takes Long positions when the price is above the 200-period SMA, ensuring we only buy dips in a confirmed uptrend. ML Correlation Filter: A Machine Learning-inspired module that analyzes the correlation between RSI and Volatility (ATR). It only permits entries when market internal dynamics suggest a reversal is technically "healthy." 3. Institutional Risk Management This script is built for "safety-first" automation: Hard Stop Loss: Fixed at 1.5% to protect against sudden market shocks. Active Trailing: A dual-trigger trailing stop. It activates once the price touches the 20 SMA (The Mean) OR once a trade reaches a 0.50% profit threshold. This ensures near-winners are protected and large runners are captured. Intraday Circuit Breaker: Includes a Max Daily Drawdown (2%) limit. If hit, the script automatically closes losing positions and halts trading for the day, while allowing winning positions to continue. Key Features Session-Specific: Tailored for the US Trading Session (UTC/NY times). Zero Overnight Risk: Automatically flattens all positions before the market close (16:00 NY Time). Holiday Intelligence: Hard-coded logic for US Market Holidays and Early Closes (2026–2028), ensuring the bot doesn't get stuck in illiquid holiday markets. Hourly Entry Cap: Limits entries to one per hour to prevent over-concentration during a single price leg. How to Use Timeframe: I suggest you use it on the 5-minute or 1-hour timeframe for optimal results. Instrument: Designed for the S&P 500, but highly effective on SPY, IVV, and ES (Futures). Pyramiding: Designed to handle up to 3 concurrent positions, allowing the strategy to scale into a move as the Z-Score deepens. Automation Ready This script is fully compatible with webhook-based automation tools. All signals (Entry, SL, Trail, Market Close, and Daily Limit) are clearly labeled in the Alert comments for seamless execution. I haven't tasted it though. This is not financial advice. Please perform your own tests and manage your risk. Disclaimer Past performance does not guarantee future results. This script is a tool for quantitative analysis and should be used as part of a broader diversified trading plan.
กลยุทธ์ Pine Script®
โดย CocoChoco1
ATR-Based Z-Score (with Signal Line)The ATR-Based Z-Score is an advanced, volatility-normalized oscillator designed to identify extreme price deviations more reliably than the standard Z-Score. By replacing the traditional Standard Deviation with the Average True Range (ATR) in the denominator, this indicator eliminates the "volatility paradox" where rapid price spikes cause standard oscillators to prematurely return to zero, even as the price continues to crash. Why this version is superior In a classic Z-Score calculation: Z = (Price - SMA) / (Standard Deviation) A sudden impulsive price drop causes the Standard Deviation to explode. Because you are dividing by a rapidly increasing number, the Z-Score often "rises" while the price is still falling. The ATR-Based Solution: Z = (Price - SMA) / ATR By using a long-period ATR as the denominator, the volatility measure remains stable and "clean." This ensures that the indicator’s troughs align much more accurately with actual price bottoms, staying in the oversold territory until the momentum truly shifts. Key Features Volatility Cleaning: The ATR-normalization prevents the indicator from "flattening out" during impulsive price movements. Integrated Signal Line: A customizable Moving Average of the Z-Score values helps filter noise and confirms entry/exit points. Independent Periods: You can set the Price MA (responsiveness) and the ATR (volatility baseline) separately to fine-tune the indicator to different timeframes. How to Trade with it 1. Mean Reversion (Buy the Dip / Sell the Rip) Long: Wait for the Z-Score to drop below a significant level (e.g., -10.0). Enter when the Z-Score crosses back above its Signal Line. Short: Wait for the Z-Score to rise above +10.0 and enter when it crosses below the Signal Line. 2. Breakout Trading A strong push of the Z-Score beyond the +/- 7.0 levels can indicate a powerful trend breakout. In this case, the Signal Line crossover serves as an effective Exit Signal, telling you that the initial momentum of the breakout is fading. Summary ✅ This indicator is designed for traders who find standard oscillators too "nervous" during volatile periods. By decoupling price deviation from immediate variance spikes, the ATR-Based Z-Score provides a rock-solid foundation for identifying true market extremes and high-probability reversal points.
อินดิเคเตอร์ Pine Script®
โดย muth96
House Rules SuperTrend Strategy (ATR-Based, Non-Repainting)📝 DESCRIPTION Overview The House Rules SuperTrend Strategy is a clean, rule-based trading strategy built using Pine Script® v6. It is designed for transparent backtesting, non-repainting signals, and simple trend-following execution across all markets and timeframes. This strategy uses TradingView’s built-in SuperTrend indicator, which is derived from Average True Range (ATR), to identify trend direction changes and generate long and short trades. How the Strategy Works Long Entry A long position is opened when the SuperTrend flips from bearish to bullish This confirms a potential upward trend shift Short Entry A short position is opened when the SuperTrend flips from bullish to bearish This confirms a potential downward trend shift Exits Positions are closed when either: The opposite SuperTrend signal appears, or The ATR-based Stop Loss or Take Profit is reached (if enabled) All signals are calculated on confirmed candle closes only, ensuring accurate and fair backtesting. Risk Management Optional ATR-based Stop Loss Optional ATR-based Take Profit Position sizing based on percentage of equity Commission included for realistic performance results All parameters are user-adjustable from the settings panel. Backtesting & Transparency This is a strategy, not an indicator No repainting No future data usage No hidden filters No lookahead bias Fully compatible with TradingView’s Strategy Tester Users are encouraged to test different symbols, timeframes, and parameter values to suit their trading style. Recommended Use This strategy can be used on: Cryptocurrencies Forex Stocks Indices Futures It performs best in trending market conditions and may underperform during low-volatility or ranging markets. Disclaimer This script is provided for educational and research purposes only. It is not financial advice. Always test and validate strategies before using them in live trading.
กลยุทธ์ Pine Script®
โดย JaxonJackFX
OrangePulse v3.0 Lite - Educational DCA StrategyThis open-source script is a simplified version of the OrangePulse algorithm, designed for educational purposes to demonstrate the power of Dollar Cost Averaging (DCA) and Mean Reversion. 📈 Strategy Logic: The script uses a combination of Bollinger Bands and RSI (Relative Strength Index) to identify potential mean reversion opportunities. - Entry: Triggered when price pushes below the lower Bollinger Band while RSI is in oversold territory. - Management: Utilizes up to 3 Safety Orders (DCA) to improve the average entry price during pullbacks. 🎯 Features: • Customizable Volume Scale and Step Scale for Safety Orders. • Visual AVG price line and TP/SL levels. • Time-window filter for backtesting. • Real-time Status Table for position monitoring. This script is shared in the spirit of open-source development on TradingView. It is intended to help traders understand how automated position building and risk management work in volatile markets. Check my profile status/bio for more information on our project. ⚠️ Disclaimer: For educational purposes only. Past performance does not guarantee future results.
กลยุทธ์ Pine Script®
โดย OrangePulse