Inizia

Indicatori e strategie

TRADSYS24-06TTTrading de SPX long and short using a Leading TIMEWAVES indicator, yo know direction of trends before they happen Bottom line is that FUTURE TRENDS of SPX are traded, which already are calculated in advance using physics law, how exactly is a secret. Proprietary software calculates a TIMEWAVES indicator far ahead in the future, which thus is a leading indicator. If this indicator is going UP in the future (strong move) then the SPX will follow and prices will go UP. If indicator goes down (strong move) the SPX will go down. Indicator is shown in TV, however, in spite of the fact it is already known for the future, this cannot be shown in TV. TV only shows time up to NOW, not all of next month in the future. Why ? because 90 % of people and vested interests in finance world always tell "nobody knows the future". Start believing the impossible like GANN, Armstrong and renaissance group and there you go.
Strategia Pine Script®
di TimeWaves
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545Strategy Overview  AlgoChadLin's BITCOIN H1 Breakout Strategy No.545 is a sophisticated breakout trading system designed for Bitcoin on the H1 timeframe. It integrates multiple volatility and price action indicators to identify high-probability breakout opportunities, aiming to capitalize on significant market movements. Auther: @algochadlin  Strategy Logic  Breakout Confirmation: Utilizes a combination of Average True Range (ATR) and Bollinger Bands to identify periods of low volatility followed by sharp price movements.  Long: Initiated when the price breaks above the previous hour's upper Bollinger Band, with ATR confirming increased volatility.  Short: Triggered when the price breaks below the previous hour's lower Bollinger Band, with ATR indicating heightened volatility.  Parameters  Price Entry Multiplier: Adjusts the entry price relative to the breakout level. Exit After Bars: Specifies the number of bars to hold the position before exiting. Profit Target (%): Defines the percentage gain at which to take profit. Stop Loss Coefficient: Multiplier for ATR to calculate stop-loss distance. Trailing Stop Coefficients: Defines the trailing stop parameters. Biggest Range Period: Determines the lookback period for identifying the largest price range.  Setup  Timeframe: 1-Hour (H1) Asset: Bitcoin, also suitable for ETH
Strategia Pine Script®
di Lin-Changhua
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range Overview: This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets. 🔍 Strategy Components: EMA Crossover (Fast/Slow) Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum. RSI Filter RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met. Long entry requires RSI ≥ Long Threshold Short entry requires RSI ≤ Short Threshold ATR-Based SL & TP Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price. Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure. Opening Range Filter (Optional) If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves. Session Filters No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods. All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options. ⚙️ Built-in Presets: You can choose one of the built-in ticker-specific presets for optimal conditions: Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL SPY 8/28 56 / 26 14 1.4× 4.0× TSLA 23/27 56 / 33 13 1.4× 3.6× AAPL 6/13 61 / 26 23 1.4× 2.1× MSFT 25/32 54 / 26 14 1.2× 2.2× META 25/32 53 / 26 17 1.8× 2.3× AMZN 28/32 55 / 25 16 1.8× 2.3× You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences. 📌 Best Use Case: This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
Strategia Pine Script®
di olaszvandor
RAHA Strategy with Dynamic TP/SL + Volatility Filter RAHA Indicator RAHA – Roni's Adjusted Hybrid Average is a unique average that neutralizes outliers from a price series, in order to provide a more reliable and stable picture of the market trend. 💡 What makes it unique? Unlike a regular average (like SMA), the RAHA indicator calculates the average only based on "normal" prices – while statistically filtering out outliers. 📈 Main uses: Identifying a smooth trend over time Reducing problematic market noise Basis for smart trading strategies RAHA Strategy – Roni's Adjusted Hybrid Average The RAHA strategy is based on a smart average (RAHA – Roni's Adjusted Hybrid Average), which channels outliers from the historical price to create a more stable trend indication. It combines: Average crossing – short SMA (10 days) versus long RAHA (20 days). Strict filters – such as a positive RAHA slope, a positive market trend according to a 60-day moving average, and a monthly RSI rising or above 70. Smart entry – only when there is high volatility (a significant gap between RAHA and SMA) or a green candle below the Bollinger band. Dynamic stop – below the low of a descending candle sequence. Profit target – set at 3 times the stop, but a trade is not closed at the TP but only according to additional specified conditions. Smart exit conditions – such as a downward crossing of the SMA or breaking a previous low. Multiple trade filtering – a time difference of at least 10 candles between trades. The strategy aims to target trades only during times of a clear trend and high volatility, while reducing sensitivity to market noise and false trades. אינדיקטור RAHA RAHA – Roni's Adjusted Hybrid Average הוא ממוצע ייחודי שמנטרל ערכים חריגים מתוך סדרת מחירים (Outliers), במטרה לספק תמונה אמינה ויציבה יותר של מגמת השוק. 💡 מה מייחד אותו? בניגוד לממוצע רגיל (כמו SMA), אינדיקטור RAHA מחשב את הממוצע רק על בסיס המחירים "הנורמליים" – תוך סינון סטטיסטי של חריגים. 📈 שימושים עיקריים: זיהוי מגמה חלקה לאורך זמן הפחתת רעשי שוק בעייתיים בסיס לאסטרטגיות מסחר חכמות אסטרטגיית RAHA – Roni's Adjusted Hybrid Average אסטרטגיית RAHA מבוססת על ממוצע חכם (RAHA – Roni's Adjusted Hybrid Average), אשר מתעל ערכים חריגים מהמחיר ההיסטורי ליצירת אינדיקציה יציבה יותר למגמה. היא משלבת בין: חציית ממוצעים – SMA קצר (10 ימים) לעומת RAHA ארוך (20 ימים). פילטרים מחמירים – כמו שיפוע RAHA חיובי, מגמת שוק חיובית לפי ממוצע נע של 60 יום, ו‑RSI חודשי עולה או מעל 70. כניסה חכמה – רק כאשר יש תנודתיות גבוהה (פער משמעותי בין RAHA ל‑SMA) או נר ירוק מתחת לרצועת בולינגר. סטופ דינמי – מתחת לנמוך של רצף נרות יורדים. יעד רווח – מוגדר לפי פי 3 מהסטופ, אך עסקה לא נסגרת ב‑TP אלא רק לפי תנאים נוספים שנקבעו. תנאי יציאה חכמים – כמו חצייה כלפי מטה של SMA או שבירת שפל קודם. סינון עסקאות מרובות – הפרש זמן של 10 נרות לפחות בין עסקאות. האסטרטגיה שואפת למקד עסקאות רק בזמנים של מגמה מובהקת ותנודתיות גבוהה, תוך הפחתת רגישות לרעש שוק ועסקאות שווא.
Strategia Pine Script®
di RoniPesach
3
Operator Levels by Trade InsiderOperator Levels by Trade Insider Overview Operator Levels by Trade Insider is a breakout trading strategy designed for intraday trading on the Nifty 50 index using a 5-minute timeframe. It identifies high-probability trade setups based on the first 5-minute candle’s price range of the day, generating target levels for long and short positions. The strategy uses a customizable Simple Moving Average (SMA) for trend filtering and a strict 1:1.5 risk-to-reward validation, making it ideal for intraday traders in the Indian equity market. Key Features Dynamic Target Levels: Plots two sets of target levels above and below the first 5-minute candle’s range, calculated using a proprietary volatility-based multiplier to project realistic price objectives. Trend Filtering: Uses a user-adjustable SMA (default: 24 periods) to ensure entries align with the prevailing market trend, reducing false breakouts. Risk-to-Reward Validation: Only executes trades with a minimum 1:1.5 risk-to-reward ratio, promoting disciplined risk management. Clean Visualization: Displays target levels as dashed lines with color-coded labels for easy identification of trade exits (Target 1, Target 2, Stop-Loss). Customizable Settings: Allows adjustment of SMA period, position size, and risk parameters to suit different trading styles and market conditions. What Makes It Unique? Unlike standard breakout strategies, Operator Levels employs a proprietary multiplier derived from volatility analysis to optimize target levels for the Nifty 50’s intraday movements. The adjustable SMA period and strict 1:1.5 risk-to-reward filter enhance entry precision, reducing noise compared to traditional range breakout systems. The strategy’s minimalist design ensures actionable signals without overwhelming the chart, tailored specifically for the fast-paced 5-minute timeframe. How to Use Setup: Apply on a 5-minute chart for the Nifty 50 index (e.g., NSE:NIFTY). Recommended for intraday trading. Default Settings: Position Size: 5% of equity per trade (adjustable via default_qty_value). SMA Period: 24 (adjustable; e.g., set to 12 for faster signals or 50 for smoother trends). Risk-to-Reward: 1:1.5 minimum for all trades. Trading Process: Long Entry: Triggered when price breaks above the first 5-minute candle’s high, is above the SMA, and meets the 1:1.5 risk-to-reward ratio. Short Entry: Triggered when price breaks below the first 5-minute candle’s low, is below the SMA, and meets the 1:1.5 risk-to-reward ratio. Exits: Close positions at Target 1, Target 2, or Stop-Loss, with alerts set via TradingView for real-time notifications. Integration: Combine with volume analysis or support/resistance indicators (e.g., RSI, pivot points) for confirmation of breakouts. Example: On a Nifty 50 5-minute chart, enter a long trade when price breaks above the first candle’s high and is above the 24-period SMA, targeting the first dashed blue line (Target 1) with a stop-loss at the first candle’s low. Backtesting Results Test Parameters: Symbol: NSE:NIFTY, 5-minute timeframe Period: 6 months (January 2025–June 2025) Initial Capital: $10,000 Commission: 0.1% per trade Slippage: 5 ticks Risk per Trade: 5% of equity Results: Total Trades: 150 Win Rate: 62% Average Risk-to-Reward: 1.5:1 Notes: Results are based on standard candles to ensure realistic performance. Backtest on your preferred timeframe and symbol to validate suitability. Limitations Trade Frequency: The 5-minute timeframe generates more trades than daily charts but may still require active market sessions (e.g., 9:15 AM–3:30 PM IST) for optimal results. Market Conditions: Breakouts may underperform in low-volatility or ranging markets; use additional confirmation (e.g., volume spikes or Nifty 50 futures data) to filter signals. Risk Management: While the 1:1.5 risk-to-reward ratio is conservative, traders should back test and adjust position sizing and SMA period to match their risk tolerance.
Strategia Pine Script®
di Trade_Insider
VolatilityGuard Scalper (Sin Restricciones Horarias)(Trend Reversals) Description: VolatilityGuard Scalper is a scalping strategy designed to capture retracements in strong trends, optimized for volatile markets such as cryptocurrencies (BTC, ETH), gold (XAU/USD), S&P 500 and DAX 40 futures. It uses a 30-period EMA to identify the trend, retracement zones based on price action, and volume filters (1.2x 30-bar SMA) and spread (maximum 15 pips) to trade only in optimal conditions. With a robust risk management (stop-loss 2x ATR, take-profit 1.8x ATR, trailing stop), it is ideal for intraday traders without time restrictions. Main Features: Indicators: 30-period EMA to define up/down trends. Recoil zones calculated with maximum/minimum of 3 bars. Above average volume (1.2x 30-bar SMA). ATR (14) for stop-loss, take-profit and trailing stop. Maximum spread filter (15 pips). Tickets: Buy: Uptrend (price > EMA, EMA going up), price in retracement zone, high volume, acceptable spread. Sell: Downtrend (price < EMA, EMA going down), price in retracement zone, high volume, acceptable spread. Risk Management: Stop-loss: 2x ATR from the entry price. Take-profit: 1.8x ATR from the entry price. Trailing stop: 1x ATR with 0.5x ATR offset. Risk per operation: 0.5% of the capital (adjustable). Dynamic position size based on ATR and spread. Markets and Time Frames: BTC: 2H (86% correct) to 4H (90% correct, recommended) DAX40:https://www.tradingview.com/x/vGlk1lxG/
Strategia Pine Script®
di Mastergio
RFM Strategy - High QualityI trade high-probability resistance fades using a systematic 4-pillar approach that has delivered a proven 60%+ win rate with 2.5+ profit factor." 📊 Core Strategy Elements: 1. VRF Resistance Identification: Multiple resistance level confluence (minimum 2 levels) Dynamic resistance zones using 20-period high/low ranges Only trade when price approaches clustered resistance 2. Volume Weakness Confirmation: Volume ROC must be ≤ -30% (weak buying pressure) Identifies exhaustion rallies with poor participation Confirms institutional selling vs retail buying 3. Momentum Divergence: SMI ≥ 60 (extreme overbought) OR 25-point momentum collapse Multi-timeframe confirmation for higher reliability Catches momentum exhaustion at key levels 4. Price Rejection Patterns: Long upper wicks (2x body size) at resistance Doji formations showing indecision Failed breakout patterns with immediate rejection ⚡ Execution: Entry: Only when ALL 4 conditions align simultaneously Risk Management: 6-point stops, 12-point targets (2:1 R/R minimum) Timeframe: 5-minute charts for precise entries Selectivity: Quality over quantity - average 5 trades per period 🏆 Performance: 60% win rate (matches manual trading performance) 2.59 Profit Factor (highly profitable) Systematic approach eliminates emotional decisions "This strategy automates the discretionary resistance fade setups that institutional traders use, with strict filters ensuring only the highest-probability opportunities."
Strategia Pine Script®
di jacdan1018
HMA Crossover + ATR + Curvature (Long & Short)📏 Hull Moving Averages (Trend Filters) - fastHMA = ta.hma(close, fastLength) - slowHMA = ta.hma(close, slowLength) These two HMAs act as dynamic trend indicators: - A bullish crossover of fast over slow HMA signals a potential long setup. - A bearish crossunder triggers short interest. ⚡️ Curvature (Acceleration Filter) - curv = ta.change(ta.change(fastHMA)) This calculates the second-order change (akin to the second derivative) of the fast HMA — effectively the acceleration of the trend. It serves as a filter: - For long entries: curv > curvThresh (positive acceleration) - For short entries: curv < -curvThresh (negative acceleration) It helps eliminate weak or stagnating moves by requiring momentum behind the crossover. 📈 Volatility-Based Risk Management (ATR) - atr = ta.atr(atrLength) - stopLoss = atr * atrMult - trailStop = atr * trailMult These define your: - Initial stop loss: scaled to recent volatility using ATR and atrMult. - Trailing stop: also ATR-scaled, to lock in gains dynamically as price moves favorably. 💰 Position Sizing via Risk Percent - capital = strategy.equity - riskCapital = capital * (riskPercent / 100) - qty = riskCapital / stopLoss This dynamically calculates the position size (qty) such that if the stop loss is hit, the loss does not exceed the predefined percentage of account equity. It’s a volatility-adjusted position sizing method, keeping your risk consistent regardless of market conditions. 📌 Execution Logic - Long Entry: on bullish HMA crossover with rising curvature. - Short Entry: on bearish crossover with falling curvature. - Exits: use ATR-based trailing stops. - Position is closed when trend conditions reverse (e.g., bearish crossover exits the long). This framework gives you: - Trend-following logic (via HMAs) - Momentum confirmation (via curvature) - Volatility-aware execution and exits (via ATR) - Risk-controlled dynamic sizing Want to get surgical and test what happens if we use curvature on the difference between HMAs instead? That might give some cool insights into trend strength transitions.
Strategia Pine Script®
di emilio_sforza
6
Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description Overview The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes. Performance Highlight: In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior. The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well. ## Key Innovation & Originality This strategy introduces a unique **dual scoring system** approach: - **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria - **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions. ## Technical Foundation ### Optimized Indicator Parameters The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns: **MACD Configuration (3,10,3)**: - Fast EMA: 3 periods (vs standard 12) - Slow EMA: 10 periods (vs standard 26) - Signal Line: 3 periods (vs standard 9) - **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility **RSI Configuration (21-period)**: - Length: 21 periods (vs standard 14) - Oversold: 30 level - Extreme Oversold: 25 level - **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment **Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance. ### Scoring System Methodology **Entry Score Components (Minimum 13 points required)**: 1. **RSI Signals** (max 5 points): - RSI < 30: +2 points - RSI < 25: +2 points - RSI turning up: +1 point 2. **MACD Signals** (max 8 points): - MACD below zero: +1 point - MACD turning up: +2 points - MACD histogram improving: +2 points - MACD bullish divergence: +3 points 3. **Price Action** (max 4 points): - Long lower wick (>50%): +2 points - Small body (<30%): +1 point - Bullish close: +1 point 4. **Pattern Recognition** (max 8 points): - RSI bullish divergence: +4 points - Quick recovery pattern: +2 points - Reversal confirmation: +4 points **Exit Score Components (Minimum 13 points required)**: Uses inverse criteria to identify swing tops with similar weighting system. ## Risk Management Features ### Position Sizing & Risk Control - **Single Position Strategy**: 100% equity allocation per trade - **No Overlapping Positions**: Ensures focused risk management - **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets ### Stop Loss & Take Profit Logic - **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer - **Risk-Based Take Profit**: Calculated using risk/reward ratio - **Clean Exit Logic**: Prevents conflicting signals ## Default Settings Optimization ### Key Parameters (Optimized for MSTR/Bitcoin-style volatility): - **Minimum Entry Score**: 13 (ensures high-conviction entries) - **Minimum Exit Score**: 13 (prevents premature exits) - **Risk/Reward Ratio**: 5.0 (accounts for volatility) - **Lower Wick Threshold**: 50% (identifies true hammer patterns) - **Divergence Lookback**: 8 bars (optimal for swing timeframes) ### Why These Defaults Work for MSTR: 1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation 2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets 3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks 4. **21-period RSI**: Reduces noise while maintaining sensitivity ## Visual Features ### Score Display System - **Green Labels**: Entry scores ≥10 points (below bars) - **Red Labels**: Exit scores ≥10 points (above bars) - **Large Triangles**: Actual trade entries/exits - **Small Triangles**: Reversal pattern confirmations ### Chart Cleanliness - Indicators plotted in separate panes (MACD, RSI) - TP/SL levels shown only during active positions - Clear trade markers distinguish signals from actual trades ## Backtesting Specifications ### Realistic Trading Conditions - **Commission**: 0.1% per trade - **Slippage**: 3 points - **Initial Capital**: $1,000 - **Account Type**: Cash (no margin) ### Sample Size Considerations - Strategy designed for 100+ trade sample sizes - Recommended timeframes: 4H, 1D for swing trading - Optimal for trending/volatile markets ## Strategy Limitations & Considerations ### Market Conditions - **Best Performance**: Trending markets with clear swings - **Reduced Effectiveness**: Highly choppy, sideways markets - **Volatility Dependency**: Optimized for moderate to high volatility assets ### Risk Warnings - **High Allocation**: 100% position sizing increases risk - **No Diversification**: Single position strategy - **Backtesting Limitation**: Past performance doesn't guarantee future results ## Usage Guidelines ### Recommended Assets & Timeframes - **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes - **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.) - **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments) - **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping ### Timeframe Recommendations - **Primary Scalping**: 5-minute and 15-minute charts - **Active Monitoring**: 1-minute for precise entries - **Swing Scalping**: 30-minute to 1-hour timeframes - **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities) ## Technical Requirements - **Pine Script Version**: v6 - **Overlay**: Yes (plots on price chart) - **Additional Panes**: MACD and RSI indicators - **Real-time Compatibility**: Confirmed bar signals only ## Customization Options All parameters are fully customizable through inputs: - Indicator lengths and levels - Scoring thresholds - Risk management settings - Visual display preferences - Date range filtering ## Conclusion This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets. The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets. **Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
Strategia Pine Script®
di Quant_Trading_Pro
3
KST Strategy [Skyrexio]Overview KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades. Unique Features ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation. Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions. Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold. Methodology The strategy opens long trade when the following price met the conditions: Close price is above the Alligator's jaw line Close price is above the filtering Moving average KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology) If the Choppiness Index filter is enabled its value shall be less than user defined threshold When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed. Strategy settings In the inputs window user can setup the following strategy settings: ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level) ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level) Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA) Filter MA Length (by default = 200, length for filter MA calculation) Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index) Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution) Choppiness Index Length (by default = 14, length used in Choppiness index calculation) KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology) KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) User can choose the optimal parameters during backtesting on certain price chart. Justification of Methodology Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index. The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago. ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value: KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4 ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1, ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2, ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3, ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4 Also for this indicator the signal line is calculated: Signal = SMA(KST, KST Signal Line Length) When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends. Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages: Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead. Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward. Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward. When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades. The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it. The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA. Key Features: It reacts faster to price changes than most moving averages. It is smoother and less noisy than short-term EMAs. It can be used to identify trend direction, momentum, and potential reversal points. ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction. To calculate it first of all we need to get True Range (TR), this is the greatest value among: High - Low abs(High - Previous Close) abs(Low - Previous Close) ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14. ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market. The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend. Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n) where: ΣATR(n) = sum of the Average True Range over n periods MaxHigh(n) = highest high over n periods MinLow(n) = lowest low over n periods log10 = base-10 logarithm Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning. Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value. When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close. Backtest Results Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions. Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks. Initial capital: 10000 USDT Percent of capital used in every trade: 60% Maximum Single Position Loss: -5.53% Maximum Single Profit: +8.35% Net Profit: +5175.20 USDT (+51.75%) Total Trades: 120 (56.67% win rate) Profit Factor: 1.747 Maximum Accumulated Loss: 1039.89 USDT (-9.1%) Average Profit per Trade: 43.13 USDT (+0.6%) Average Trade Duration: 27 hours These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. How to Use Add the script to favorites for easy access. Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT). Configure settings using the dropdown choice list in the built-in menu. Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}} Disclaimer: Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Strategia Pine Script®
di Skyrexio
Ticker Pulse Meter + Fear EKG StrategyDescription The Ticker Pulse Meter + Fear EKG Strategy is a technical analysis tool designed to identify potential entry and exit points for long positions based on price action relative to historical ranges. It combines two proprietary indicators: the Ticker Pulse Meter (TPM), which measures price positioning within short- and long-term ranges, and the Fear EKG, a VIX-inspired oscillator that detects extreme market conditions. The strategy is non-repainting, ensuring signals are generated only on confirmed bars to avoid false positives. Visual enhancements, such as optional moving averages and Bollinger Bands, provide additional context but are not core to the strategy's logic. This script is suitable for traders seeking a systematic approach to capturing momentum and mean-reversion opportunities. How It Works The strategy evaluates price action using two key metrics: Ticker Pulse Meter (TPM): Measures the current price's position within short- and long-term price ranges to identify momentum or overextension. Fear EKG: Detects extreme selling pressure (akin to "irrational selling") by analyzing price behavior relative to historical lows, inspired by volatility-based oscillators. Entry signals are generated when specific conditions align, indicating potential buying opportunities. Exits are triggered based on predefined thresholds or partial position closures to manage risk. The strategy supports customizable lookback periods, thresholds, and exit percentages, allowing flexibility across different markets and timeframes. Visual cues, such as entry/exit dots and a position table, enhance usability, while optional overlays like moving averages and Bollinger Bands provide additional chart context. Calculation Overview Price Range Calculations: Short-Term Range: Uses the lowest low (min_price_short) and highest high (max_price_short) over a user-defined short lookback period (lookback_short, default 50 bars). Long-Term Range: Uses the lowest low (min_price_long) and highest high (max_price_long) over a user-defined long lookback period (lookback_long, default 200 bars). Percentage Metrics: pct_above_short: Percentage of the current close above the short-term range. pct_above_long: Percentage of the current close above the long-term range. Combined metrics (pct_above_long_above_short, pct_below_long_below_short) normalize price action for signal generation. Signal Generation: Long Entry (TPM): Triggered when pct_above_long_above_short crosses above a user-defined threshold (entryThresholdhigh, default 20) and pct_below_long_below_short is below a low threshold (entryThresholdlow, default 40). Long Entry (Fear EKG): Triggered when pct_below_long_below_short crosses under an extreme threshold (orangeEntryThreshold, default 95), indicating potential oversold conditions. Long Exit: Triggered when pct_above_long_above_short crosses under a profit-taking level (profitTake, default 95). Partial exits are supported via a user-defined percentage (exitAmt, default 50%). Non-Repainting Logic: Signals are calculated using data from the previous bar ( ) and only plotted on confirmed bars (barstate.isconfirmed), ensuring reliability. Visual Enhancements: Optional moving averages (SMA, EMA, WMA, VWMA, or SMMA) and Bollinger Bands can be enabled for trend context. A position table displays real-time metrics, including open positions, Fear EKG, and Ticker Pulse values. Background highlights mark periods of high selling pressure. Entry Rules Long Entry: TPM Signal: Occurs when the price shows strength relative to both short- and long-term ranges, as defined by pct_above_long_above_short crossing above entryThresholdhigh and pct_below_long_below_short below entryThresholdlow. Fear EKG Signal: Triggered by extreme selling pressure, when pct_below_long_below_short crosses under orangeEntryThreshold. This signal is optional and can be toggled via enable_yellow_signals. Entries are executed only on confirmed bars to prevent repainting. Exit Rules Long Exit: Triggered when pct_above_long_above_short crosses under profitTake. Partial exits are supported, with the strategy closing a user-defined percentage of the position (exitAmt) up to four times per position (exit_count limit). Exits can be disabled or adjusted via enable_short_signal and exitPercentage settings. Inputs Backtest Start Date: Defines the start of the backtesting period (default: Jan 1, 2017). Lookback Periods: Short (lookback_short, default 50) and long (lookback_long, default 200) periods for range calculations. Resolution: Timeframe for price data (default: Daily). Entry/Exit Thresholds: entryThresholdhigh (default 20): Threshold for TPM entry. entryThresholdlow (default 40): Secondary condition for TPM entry. orangeEntryThreshold (default 95): Threshold for Fear EKG entry. profitTake (default 95): Exit threshold. exitAmt (default 50%): Percentage of position to exit. Visual Options: Toggle for moving averages and Bollinger Bands, with customizable types and lengths. Notes The strategy is designed to work across various timeframes and assets, with data sourced from user-selected resolutions (i_res). Alerts are included for long entry and exit signals, facilitating integration with TradingView's alert system. The script avoids repainting by using confirmed bar data and shifted calculations ( ). Visual elements (e.g., SMA, Bollinger Bands) are inspired by standard Pine Script practices and are optional, not integral to the core logic. Usage Apply the script to a chart, adjust input settings to suit your trading style, and use the visual cues (entry/exit dots, position table) to monitor signals. Enable alerts for real-time notifications. Designed to work best on Daily timeframe.
Strategia Pine Script®
di chuckaschultz
Baseline TrendBaseline Trend Strategy Overview Baseline Trend is a crypto-only trading strategy built on straightforward price-based logic: market direction is determined solely by the price’s position relative to a selected baseline open price. No technical indicators like RSI, MACD, or volume are used—this approach is purely focused on price action and position size manipulation. This strategy is a genuine concept, developed from my own market analysis and logical theory, refined through extensive observation of crypto market behaviour. While the strategy offers structure and adaptability, it’s important to recognise that no single trading system or indicator fits all market conditions. This tool is meant to support decision-making, not replace it—encouraging traders to stay flexible, informed, and in control of their risk. Important Usage Note: This system is intended for crypto markets only. – When used as an indicator guide, it can be applied to both spot and futures markets. – However, when used with web-hook automation, it is designed only for futures contracts. Ensure compatibility with your trading setup before using automation features. Core Logic: The Baseline The strategy revolves around the concept of a “Baseline”, with three types available: Main Baseline: Defines the primary trend direction. If the price is above, go long; if below, go short. Second Baseline and Third Baseline: Used to measure buying/selling pressure and are key to certain take-profit logic options. Baselines are customisable to different timeframes—Year, Month, Week, and more—based on available input settings. Structurally, the Main Baseline is the highest-level trend reference, followed by the Second, then Third. Users can mix and match these baselines across timeframes to backtest crypto symbols and understand behaviour patterns, particularly when used with standard candlestick charts. Entry & Exit Logic Entry Signal: Triggered when price crosses over/under a defined distance (percentage) from the Main Baseline. This distance is the Trade Line, calculated based on the close price. Exit Signal / Stop Loss: If price moves un-favorable and crosses over/under the Stop Loss Line (a defined distance from the Main Baseline), the open position will be force-closed according to user-defined settings. LiqC (Liquidation Cut) LiqC is a secondary stop-loss that activates when a leveraged position’s loss equals or exceeds the user-defined liquidation threshold. It forcefully closes the position to help prevent full liquidation before stop-loss, providing an extra layer of protection. This LiqC is directly tied to the leverage level set by the user. Please ensure you understand how leverage affects liquidation risk, as different broker exchanges may use different liquidation ratio models. Using incorrect assumptions or mismatched leverage values may result in unexpected behaviour. Position Sizing & Block Units This strategy features a block-based position sizing system designed for flexibility and precision in trade management: Block Range: Customisable from 1 to 10 blocks Risk Allocation: Controlled through a user-defined ROE (Risk of Equity) value For example, setting an ROE of 0.1% with 10 blocks allocates a total of 1% of account equity to the position. This structure supports both conservative and aggressive risk approaches, depending on user preference. Block sizes are automatically calculated in alignment with exchange requirements, using Minimum Notional Value (MNV) and Minimum Trade Amount (MTA). These values are dynamically calculated based on the live market price, and scaled relative to the trader’s balance and selected risk percentage. This ensures accurate sizing with built-in adaptability for any account level and current market conditions. Scalping Meets Trend Holding This system blends short-term scalping with longer-term trend holding, offering a flexible and adaptive trading style. Example: Enter 10 blocks → take quick profits on 5 blocks → let the remaining 5 ride the trend. This dual-layered approach allows traders to secure early gains while staying positioned for larger market moves. Think of it as: 5 Blocks to Protect: Capture quick wins and manage exposure. 5 Blocks to Pursue: Let profits run by following the broader trend. By combining both protection and pursuit, the strategy supports risk control without sacrificing the potential for extended returns. Flexible Take-Profit Logic The strategy supports multiple, customisable take-profit mechanisms: TP1–4 (Profit Percentage) Triggers take profit of 1 block unit when unrealised gains reach defined percentage thresholds (TP1, TP2, TP3, TP4). Buying/Selling Pressure-Based Take Profit D1 – Pressure 1 Measures pressure between Second and Third Baselines. If the distance between them exceeds a user-defined DPT (Decrease Post Threshold) and the price moves far enough from the Third Baseline, D1 activates to take profit or scale out one block. D2 – Pressure 2 Measures pressure between the Main and Second Baselines. Works similarly to D1, using a separate distance and pressure trigger. Note: Both D1 and D2 deactivate in reversal or even trend conditions. D3–5: High-High / Low-Low Logic Based on bar index tracking after position entry: For Long Positions: If after D3 bars the price doesn't exceed the previous bar's high, the system executes a take profit or scale-out. For Short Positions: If the price doesn't drop below the previous low, the same logic applies. This approach adds time-based and momentum-aware exit flexibility. Leverage & Liquidation Risk When backtesting with leverage enabled, the system checks whether historical candles exceed the liquidation range, calculated based on the average entry price and the leverage input. If the Liquidation Risk Count exceeds 1, profit and loss accuracy may be affected. Traders are encouraged to monitor this count closely to ensure realistic backtesting results. Since the system cannot directly control or sync with your broker exchange’s actual leverage setting, it’s important to manually match the system’s leverage input with your broker’s configured leverage. For example: If the system leverage input is set to 10, your exchange leverage setting must also be set to 10. Any mismatch will lead to inaccurate liquidation risk and PnL calculations. Backtesting and Customisation All TP1–4 and D1–5 functions are fully optional and customisable. Users are encouraged to backtest different crypto symbols to observe how price behaviour aligns with baseline structures and pressure metrics. Each of the TP1–4 and D1–5 triggers is designed to execute only once per open position, ensuring controlled and predictable behaviour within each trade cycle. Since backtesting is based on available historical bar data, please note that data availability varies depending on your TradingView subscription plan. For more reliable insights, it’s recommended to backtest across multiple time ranges, not just the full dataset, to assess the stability and consistency of the strategy’s performance over time. Additionally, the time frame resolution interval in TradingView is customisable. For best results, use commonly supported time frames such as 30 minutes, 1 hour, 4 hours, 1 day, or 1 week. While the system is designed to support a broad range of intervals, non-standard resolutions may still cause calculation errors. Currently, the system supports the following resolution ranges: Intraday: from 1 minute to 720 minutes (e.g., 60 minutes = 1 hour, 240 minutes = 4 hours, 720 minutes = 12 hours) Daily: from 1 day to 6 days Weekly: from 1 week to 3 weeks Monthly: from 1 month to 4 months Although the script is built to adapt to various resolutions, users should still monitor output behaviour closely, especially when testing less common or edge-case time frames. System Usage Notice: This system can be used as a standalone trading indicator or integrated with an exchange that supports web-hook signal execution. If you choose to automate trades via web-hook, please ensure you fully understand how to configure the setup properly. Web-hook integration methods vary between exchanges, and incorrect setup may lead to unintended trades. Users are responsible for ensuring proper configuration and monitoring of their automation. Note on Lower Time Frame Usage When using lower time frames (e.g., 1-minute charts) as the trading time frame, please be aware that available historical data may be limited depending on your subscription plan. This can affect the depth and reliability of backtesting, making it harder to establish a trustworthy probability model for a symbol’s behaviour over time. Additionally, when pairing a high-level Main Baseline (MBL) time line (such as "1 Month") with low time frame resolutions (like 1-minute), you may encounter order execution limits or calculation overloads during backtesting. This is due to the large number of historical bars required, which can strain the system's capacity. That said, if a user intentionally chooses to work with lower time frames, that decision is fully respected—but it should be done with awareness and at the user’s own risk. Things to Be Aware Of (Web-hook Usage Only) The following points apply if you're using web-hook automation to send signals from the system to an exchange: Alert Signal Reliability During extreme market volatility, some broker exchanges may fail to respond to web-hook signals due to traffic overload. While rare, this has occurred in the past and should be considered when relying on automation. Alert Expiration (TradingView) If you're on a Basic plan, TradingView alerts are only active for a limited time—typically around 1.5 months. Once expired, signals will no longer be sent out. To keep your system active, reset the alert before expiration. For uninterrupted alerts, consider upgrading to a Premium plan, which supports permanent alert activation. TradingView Alert Maintenance TradingView may occasionally perform system maintenance, during which alerts may temporarily stop functioning. It’s recommended to monitor TradingView’s status if you’re relying on real-time automation. Repainting As of the current version, no repainting behaviour has been observed. Signal stability and consistency have been maintained across real-time and historical bars. Order Execution Type and Fill Logic All signals use Limit orders by default, except for MBL Exit and Fallback execution, which use Market orders. Since Limit orders are not guaranteed to fill, the system includes logic to cancel unfilled orders and resend them. If necessary, a Fallback Market order is used to avoid conflict with new incoming trades. This has only happened once, and is considered rare, but users should always monitor execution status to ensure accuracy and alignment with system behaviour. Feedback If you encounter any errors, bugs, or unexpected behaviour while using the system, please don’t hesitate to let me know. Your input is invaluable for helping improve the strategy in future updates. Likewise, if you have any suggestions or ideas for enhancing the system—whether it’s a new feature, adjustment, or usability improvement—please feel free to share. Together, we can continue refining the tool to make it more robust and beneficial for everyone. Disclaimer All trading involves risk, particularly in the crypto market where conditions can be highly volatile. Past performance does not guarantee future outcomes, and market behaviour may evolve over time. This strategy is offered as a tool to support trading decisions and should not be considered financial or investment advice. Each user is responsible for their own actions and accepts full responsibility for any results that may arise from using this system.
Strategia Pine Script®
di MangoLoke
5
LANZ Strategy 1.0 [Backtest]🔷 LANZ Strategy 1.0 — Time-Based Session Trading with Smart Reversal Logic and Risk-Controlled Limit Orders This backtest version of LANZ Strategy 1.0 brings precision to session-based trading by using directional confirmation, pre-defined risk parameters, and limit orders that execute overnight. Designed for the 1-hour timeframe, it allows traders to evaluate the system with configurable SL, TP, and risk settings in a fully automated environment. 🧠 Core Strategy Logic: 1. Directional Confirmation at 18:00 NY: At 18:00 NY, the system compares the 08:00 open vs the 18:00 close: If the direction matches the previous day, the signal is reversed. If the direction differs, the current day's trend is kept. This logic is designed to avoid momentum exhaustion and capture corrective reversals. 2. Entry Level Definition: Based on the confirmed direction: For BUY, the Low of the day is used as Entry Point (EP). For SELL, the High of the day becomes EP. The system plots a Stop Loss and Take Profit based on user-defined pip inputs (default: SL = 18 pips, TP = 54 pips → RR 1:3). 3. Time-Limited Entry Execution (LIMIT Orders): Orders are sent after 18:00 NY and can be triggered anytime between 18:00 and 08:00 NY. If EP is not touched before 08:00, the order is automatically cancelled. 4. Manual Close Feature: If the trade is still open at the configured hour (default 09:00 NY), the system closes all positions, simulating realistic intraday exit scenarios. 5. Lot Size Calculation Based on Risk: Lot size is dynamically calculated using the account size, risk percentage, and SL distance. This ensures consistent risk exposure regardless of market volatility. ⚙️ Step-by-Step Flow: 08:00 NY → Captures the open of the day. 18:00 NY → Confirms direction and defines EP, SL, and TP. After 18:00 NY → If conditions are met, a LIMIT order is placed at EP. Between 18:00–08:00 NY → If price touches EP, the trade is executed. At 08:00 NY → If EP wasn’t touched, the order is cancelled. At Configured Manual Close Time (default 09:00 NY) → All open positions are force-closed if still active. 🧪 Backtest Settings: Timeframe: 1-hour only Order Type: strategy.entry() with limit= SL/TP Configurable: Yes, in pips Risk Input: % of capital per trade Manual Close Time: Fully adjustable (default 09:00 NY) 👨‍💻 Credits: Developed by LANZ Strategy logic and trading concept built with clarity and precision. Code structure and documentation by Kairos, your AI trading assistant. Designed for high-confidence execution and clean backtesting performance.
Strategia Pine Script®
di rau_u_lanz
1
Aftershock Playbook: Stock Earnings Drift EngineStrategy type Event-driven post-earnings momentum engine (long/short) built for single-stock charts or ADRs that publish quarterly results. What it does Detects the exact earnings bar (request.earnings, lookahead_off). Scores the surprise and launches a position on that candle’s close. Tracks PnL: if the first leg closes green, the engine automatically re-enters on the very next bar, milking residual drift. Blocks mid-cycle trades after a loss until the next earnings release—keeping the risk contained to one cycle. Think of it as a sniper that fires on the earnings pop, reloads once if the shot lands, then goes silent until the next report. Core signal inputs Component Default Purpose EPS Surprise % +0 % / –5 % Minimum positive / negative shock to trigger longs/shorts. Reverse signals? Off Quick flip for mean-reversion experiments. Time Risk Mgt. Off Optional hard exit after 45 calendar days (auto-scaled to any TF). Risk engine ATR-based stop (ATR × 2 by default, editable). Bar time stop (15-min → Daily: Have to select the bar value ). No pyramiding beyond the built-in “double-tap”. All positions sized as % of equity via Strategy Properties. Visual aids Yellow triangle marks the earnings bar. Diagnostics table (top-right) shows last Actual, Estimate, and Surprise %. Status-line tool-tips on every input. Default inputs Setting Value Positive surprise ≥ 0 % Negative surprise ≤ –5 % ATR stop × 2 ATR length 50 Hold horizon 350 ( 1h timeframe chart bars) Back-test properties Initial capital  10 000 Order size    5 % of equity Pyramiding    1 (internal re-entry only) Commission   0.03 % Slippage     5 ticks Fills      Bar magnifier ✔ · On bar close ✔ · Standard OHLC ✔ How to use Add the script to any earnings-driven stock (AAPL, MSFT, TSLA…). Turn on Time Risk Management if you want stricter risk management Back-test different ATR multipliers to fit the stock’s volatility. Sync commission & slippage with your broker before forward-testing. Important notes Works on every timeframe from 15 min to 1 D. Sweet spot around 30min/1h All request.earnings() & request.security() calls use lookahead_off—zero repaint. The “double-tap” re-entry occurs once per winning cycle to avoid drift-chasing loops. Historical stats ≠ future performance. Size positions responsibly.
Strategia Pine Script®
di exlux
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them. It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes. I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that. Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should). I have my own ideas of improvements which I will probably implement separately to keep this clean.
Strategia Pine Script®
di Yuri_Lopukhov
US30 Stealth StrategyOnly works on US30 (CAPITALCOM) 5 Minute chart 📈 Core Concept: This is a trend-following strategy that captures strong market continuations by entering on: The 3rd swing in the current trend, Confirmed by a volume-verified engulfing candle, With adaptive SL/TP and position sizing based on risk. 🧠 Entry Logic: ✅ Trend Filter Uses a 50-period Simple Moving Average (SMA). Buy only if price is above SMA → Uptrend Sell only if price is below SMA → Downtrend ✅ Swing Count Logic For buy: Wait for the 3rd higher low For sell: Wait for the 3rd lower high Uses a 5-bar lookback to detect highs/lows This ensures you’re not buying early — but after trend is confirmed with structure. ✅ Engulfing Candle Confirmation Bullish engulfing for buys Bearish engulfing for sells Candle must engulf previous bar completely (body logic) ✅ Volume Filter Current candle volume must be greater than the 20-period volume average Ensures trades only occur with institutional participation ✅ MA Slope Filter Requires the slope of the 50 SMA over the last 3 candles to exceed 0.1 Avoids chop or flat trends Adds momentum confirmation to the trade ✅ Session Filter (Time Filter) Trades only executed between: 2:00 AM to 11:00 PM Oman Time (UTC+4) Helps avoid overnight chop and illiquidity 📊 Position Sizing & Risk Management ✅ Smart SL (Adaptive Stop Loss) SL is based on full size of the signal candle (including wick) But if candle is larger than 25 points, SL is cut to half the size This prevents oversized risk from long signals during volatile moves.
Strategia Pine Script®
di comprehensiveA77115
PMI Nifty (Intraday) 5 Mins V2This is a Special Strategy for Nifty Intraday to be used on 5 Minutes Chart. We are not a SEBI-registered investment or financial advisor. Strategies should not be followed solely based on past performance. Profit and loss are part of the trading business and Back testing is a feature of Trading View and we show it only for informational and educational purposes. Conducting paper trading for at least one month is highly recommended to understand strategy behavior. Please note that trading strategies are not a shortcut to becoming wealthy, and a disciplined approach is essential for long-term results.
Strategia Pine Script®
di CA_Kalpesh2024
Quantum Reversal# 🧠 Quantum Reversal ## **Quantitative Mean Reversion Framework** This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**. --- ## ⚡ **Core Technical Architecture** ### 📊 **Statistical Foundation** - **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals - **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns - **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions ### 🔬 **Momentum Analysis Layer** - **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45 - **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals - **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings ### ⚙️ **Entry Logic Architecture** ``` Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45) ``` - **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry - **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity - **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure ### 🎯 **Exit Strategy Optimization** - **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L - **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion - **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels --- ## 📈 **Statistical Properties** ### **Risk Management Framework** - **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets - **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves - **Position Management**: Single position limit prevents over-leveraging ### **Signal Processing Characteristics** - **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations - **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility - **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment --- ## 🔧 **Parameter Configuration** | Technical Parameter | Value | Statistical Significance | |-------------------|-------|-------------------------| | Bollinger Period | 20 | Standard statistical lookback for volatility calculation | | Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) | | RSI Period | 14 | Traditional momentum oscillator period | | RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics | | Smoothing Period | 5 | Noise reduction filter for momentum signals | --- ## 📊 **Algorithmic Advantages** ✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets ✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions ✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives ✅ **Momentum Integration**: RSI smoothing improves signal quality and timing ✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias --- ## 🔬 **Mathematical Foundation** The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal. **Statistical Basis:** - Mean reversion follows the principle that extreme price deviations from the moving average are temporary - The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution - RSI momentum smoothing reduces noise inherent in oscillator calculations --- ## ⚠️ **Risk Considerations** This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential. --- ## 🎯 **Implementation Notes** - **Market Regime Awareness**: Most effective in ranging/consolidating markets - **Volatility Sensitivity**: Performance may vary during extreme volatility events - **Backtesting Recommended**: Historical performance analysis advised before live implementation - **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach --- **Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
Strategia Pine Script®
di ArganaBridgeCapital
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