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Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail. 1. General Description Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions. Key Features: Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes. Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses. Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes. Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold). Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle). Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results). Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio. Strategy Settings: Initial capital: $10,000. Pyramiding: Up to 3 positions. Position size: 10% of equity (default_qty_value=10). Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management. Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading. 2. Working Logic (Step by Step) The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works: a. Input Parameters The inputs are grouped for clarity: Herd Behavior (🐑): RSI Period (14): For overbought/oversold detection. Volume MA Period (20): To calculate average volume for spike detection. Herd Threshold (2.0): Volume multiplier for detecting herd activity. Liquidity Analysis (💧): Liquidity Lookback (50): Bars to check for recent highs/lows. Liquidity Sensitivity (1.5): Volume multiplier for trap detection. Institutional Flow (🏦): Institutional Volume Multiplier (2.5): For detecting large volume spikes. Institutional MA Period (21): For Accumulation/Distribution smoothing. Nash Equilibrium (⚖️): Nash Period (100): For calculating price mean and standard deviation. Nash Deviation (0.02): Multiplier for equilibrium bands. Risk Management (🛡️): Use Stop-Loss (true): Enables SL at 2% below/above entry price. Use Take-Profit (true): Enables TP at 5% above/below entry price. b. Herd Behavior Detection RSI (14): Checks for extreme conditions: Overbought: RSI > 70 (potential herd buying). Oversold: RSI < 30 (potential herd selling). Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold). Momentum: Price change over 10 bars (close - close ) compared to its SMA(20). Herd Signals: Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background). Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background). c. Liquidity Trap Detection Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback). Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones. Trap Conditions: Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5). Down Trap: Price breaks recent low, closes above it, with a volume spike. Visualization: Traps are marked with small red/green crosses above/below bars. d. Institutional Flow Analysis Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity. Accumulation/Distribution (AD): Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time. Smoothed with SMA(21) (inst_ma_length). Accumulation: AD > MA + high volume = Institutions buying. Distribution: AD < MA + high volume = Institutions selling. Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying. e. Nash Equilibrium Calculation: Price mean: SMA(100) (nash_period). Standard deviation: stdev(100). Upper Nash: Mean + StdDev x 0.02 (nash_deviation). Lower Nash: Mean - StdDev x 0.02. Conditions: Near Equilibrium: Price between upper and lower Nash bands (stable market). Above Nash: Price > upper band (overbought, sell potential). Below Nash: Price < lower band (oversold, buy potential). Visualization: Orange line (mean), red/green lines (upper/lower bands). f. Game Theory Signals The strategy generates three types of signals, combined into long/short triggers: Contrarian Signals: Buy: Herd selling + (accumulation or down trap) = Go against retail panic. Sell: Herd buying + (distribution or up trap). Momentum Signals: Buy: Below Nash + positive smart money + no herd buying. Sell: Above Nash + negative smart money + no herd selling. Nash Reversion Signals: Buy: Below Nash + rising close (close > close ) + volume > MA. Sell: Above Nash + falling close + volume > MA. Final Signals: Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy. Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell. g. Position Management Position Sizing (Minimax Principle): Default: 1.0 (10% of equity). In Nash equilibrium: Reduced to 0.5 (conservative). During institutional volume: Increased to 1.5 (aggressive). Entries: Long: If long_signal is true and no existing long position (strategy.position_size <= 0). Short: If short_signal is true and no existing short position (strategy.position_size >= 0). Exits: Stop-Loss: If use_sl=true, set at 2% below/above entry price. Take-Profit: If use_tp=true, set at 5% above/below entry price. Pyramiding: Up to 3 concurrent positions allowed. h. Visualization Nash Bands: Orange (mean), red (upper), green (lower). Background Colors: Herd buying: Red (90% transparency). Herd selling: Green. Institutional volume: Blue. Signals: Contrarian buy/sell: Green/red triangles below/above bars. Liquidity traps: Red/green crosses above/below bars. Tables: Game Theory Table (Top-Right): Herd Behavior: Buying frenzy, selling panic, or normal. Institutional Flow: Accumulation, distribution, or neutral. Nash Equilibrium: In equilibrium, above, or below. Liquidity Status: Trap detected or safe. Position Suggestion: Long (green), Short (red), or Wait (gray). Backtest Table (Bottom-Right): Total Trades: Number of closed trades. Win Rate: Percentage of winning trades. Net Profit/Loss: In USD, colored green/red. Profit Factor: Gross profit / gross loss. Max Drawdown: Peak-to-trough equity drop (%). Win/Loss Trades: Number of winning/losing trades. Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown). Avg Win/Loss Ratio: Average win per trade / average loss per trade. Last Update: Current time. i. Backtesting Metrics Tracks: Total trades, winning/losing trades. Win rate (%). Net profit ($). Profit factor (gross profit / gross loss). Max drawdown (%). Simplified Sharpe ratio (returns / drawdown). Average win/loss ratio. Updates metrics on each closed trade. Displays a label on the last bar with backtest period, total trades, win rate, and net profit. j. Alerts No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")). Use TradingView's alert system with Strategy Tester outputs. 3. Usage Tips Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals. Settings: Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping). Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets. Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto). Nash Period: Increase to 200 for longer-term analysis. Backtesting: Use TradingView's Strategy Tester to evaluate performance. Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability. Test on different assets/timeframes to ensure robustness. Live Trading: Start with a demo account. Combine with other indicators (e.g., EMAs, support/resistance) for confirmation. Monitor liquidity traps and institutional flow for context. Risk Management: Always use SL/TP to limit losses. Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading). Avoid over-leveraging (pyramiding=3 can amplify risk). Troubleshooting: If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity). Ensure sufficient historical data for Nash and liquidity calculations. If tables overlap, adjust position.top_right/bottom_right coordinates. 4. Key Differences from the Previous Indicator Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting. Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones. Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns. Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator. Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy. Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator. 5. Conclusion The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management. If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
Pine Script®策略
由EfeErdost提供
Day Trading Strategy (With Risk Management)This is a day trading strategy based on fast and slow EMA crossovers combined with RSI filtering to enhance trade accuracy. Designed for intraday use, it generates buy signals when the fast EMA crosses above the slow EMA and sell signals when it crosses below, but only if the RSI confirms momentum is favorable to avoid false entries in choppy markets. The strategy includes built-in risk management with configurable stop-loss and take-profit levels set at 1% by default, helping to limit losses and secure profits quickly within the trading day. Clear buy and sell signals are plotted on the chart, and alerts notify traders in real time when trading opportunities arise. Ideal for short-term traders, this system provides a disciplined, mechanical approach to capturing intraday trends with momentum confirmation and essential risk controls. It is fully customizable to fit different day trading instruments, timeframes, and risk appetites.
Pine Script®策略
由mnwrahmad提供
BTC 1m Chop Top/Bottom Reversal (Stable Entries)Strategy Description: BTC 5m Chop Top/Bottom Reversal (Stable Entries) This strategy is engineered to capture precise reversal points during Bitcoin’s choppy or sideways price action on the 5-minute timeframe. It identifies short-term tops and bottoms using a confluence of volatility bands, momentum indicators, and price structure, optimized for high-probability scalping and intraday reversals. Core Logic: Volatility Filter: Uses an EMA with ATR bands to define overextended price zones. Momentum Divergence: Confirms reversals using RSI and MACD histogram shifts. Price Action Filter: Requires candle confirmation in the direction of the trade. Locked Signal Logic: Prevents repaints and disappearing trades by confirming signals only once per bar. Trade Parameters: Short Entry: Above upper band + overbought RSI + weakening MACD + bearish candle Long Entry: Below lower band + oversold RSI + strengthening MACD + bullish candle Take Profit: ±0.75% Stop Loss: ±0.4% This setup is tuned for traders using tight risk control and leverage, where execution precision and minimal drawdown tolerance are critical.
Pine Script®策略
由Schedule1Cannabis提供
1
Intra Bullish Strategy - Profit Ping v4.0ProfitPing 4.0 is a high-precision intraday swing trading strategy designed for global equity markets, including the US, South Africa, and Australia. The system identifies high-probability BUY and EXIT signals using a confluence of technical indicators and real-time volume dynamics. 🧠 Key Features: Dual EMA Crossover (7 & 14) for short-term trend confirmation Volume Spike Detection based on 20-period moving average RSI Momentum Filter (ideal zone: 55–65) to avoid overbought entries MACD Histogram & Signal Line Sync for trend momentum validation Candlestick Pattern Filtering (e.g. bullish engulfing, flags, breakout candles) Multi-Timeframe Confirmation (optional) for intraday trend alignment Dynamic Risk-to-Reward Logic built into alert framework Webhook-compatible JSON alerts for automation to Google Sheets, Power BI, and IBKR 🛠️ Alert System: BUY alert triggers when all bullish conditions align EXIT alert triggers only if a previous BUY exists for that ticker Trade status is updated live in Google Sheets and integrated with Power BI dashboards Orphaned EXITs (no matched BUY) are tracked separately for accuracy review 🔄 Ideal For: Traders seeking 1:2 to 1:5 risk/reward setups Automation-focused workflows (via TradingView → Google Sheets → Power BI) Swing traders wanting clean visual logs, automated P&L tracking, and optional IBKR execution
Pine Script®策略
由mill6soon提供
Refined MA + Engulfing (M5 + Confirmed Structure Break)I would like to start by saying that this strategy was put together using ChatGPT, some past trades from myself and some backtested trades, and from my time as a student in Wallstreet Academy under Cue Banks. I am not profitable yet. I am too jumpy and blow accounts. I'm hoping this strategy (and it's indicator twin) can help me spend less time on the charts, so that I'm not tempted to press buttons as much. It does fire quite a bit. But, the Strategy Tester tab shows a 30% win rate with our wins being significant to our losses. So, in theory, if you followed the rules of this strategy STRICTLY, you COULD BE profitable. With that being said, there are times that this strategy has shown to trigger and I ask, "Why?". I just want to help myself and others, and maybe make some decent\cool stuff along the way. Enjoy KR
Pine Script®策略
由IamKRfx提供
Swing FX Pro Panel v1Description: "Swing FX Pro Panel v1" is a professional swing trading strategy tailored for the Forex market and other highly liquid assets. The core logic is based on the crossover of two Exponential Moving Averages (EMA), allowing the strategy to detect trend shifts and generate precise entry signals. The script includes an interactive performance panel that dynamically displays: initial capital, risk per trade (%), the number of trades taken during a selected period (e.g., 6 months), win/loss statistics, ROI (Return on Investment), maximum drawdown, win ratio.
Pine Script®策略
由dominikzaba提供
CVD Divergence + Volume HMA RSI MACD StrategyHow the script works: The script calculates the HMA for trend direction. The HMA (shown in orange) is used as a filter: long trades are taken only if price is above the HMA, and short trades when below. The CVD is computed by cumulatively adding volume on up bars and subtracting volume on down bars. Pivot routines (with the input "Pivot Length") detect swing lows/highs for both price and CVD. A bullish divergence is flagged when the price makes a lower low while the CVD makes a higher low. Similarly, a bearish divergence is flagged when the price makes a higher high while the CVD makes a lower high. Trading is triggered when the divergence condition also agrees with the HMA filter. Feel free to further adjust the parameters or add risk‐management/exit rules as needed for your trading style.
Pine Script®策略
由uxwrrk提供
LANZ Strategy 5.0 [Backtest]🔷 LANZ Strategy 5.0 — Rule-Based BUY Logic with Time Filter, Session Limits and Auto SL/TP Execution This is the backtest version of LANZ Strategy 5.0, built as a strategy script to evaluate real performance under fixed intraday conditions. It automatically places BUY and SELL trades based on structured candle confirmation, EMA trend alignment, and session-based filters. The system simulates real-time execution with precise Stop Loss and Take Profit levels. 📌 Built for traders seeking to simulate clean intraday logic with fully automated entries and performance metrics. 🧠 Core Logic & Strategy Conditions ✅ BUY Signal Conditions: Price is above the EMA200 The last 3 candles are bullish (close > open) The signal occurs within the defined session window (NY time) Daily trade limit has not been exceeded If all are true, a BUY order is executed at market, with SL and TP set immediately. 🔻 SELL Signal Conditions (Optional): Exactly inverse to BUY (below EMA + 3 bearish candles). Disabled by default. 🕐 Operational Time Filter (New York Time) You can fully customize your intraday window: Start Time: e.g., 01:15 NY End Time: e.g., 16:00 NY The system evaluates signals only within this range, even across midnight if configured. 🔁 Trade Management System One trade at a time per signal Trades include a Stop Loss (SL) and Take Profit (TP) based on pip distance Trade result is calculated automatically Each signal is shown with a triangle marker (BUY only, by default) 🧪 Backtest Accuracy This version uses: strategy.order() for entries strategy.exit() for SL and TP strategy.close_all() at the configured manual closing time This ensures realistic behavior in the TradingView strategy tester. ⚙️ Flow Summary (Step-by-Step) On every bar, check: Is the time within the operational session? Is the price above the EMA? Are the last 3 candles bullish? If conditions met → A BUY trade is opened: SL = entry – X pips TP = entry + Y pips Trade closes: If SL or TP is hit Or at the configured manual close time (e.g., 16:00 NY) 📊 Settings Overview Timeframe: 1-hour (ideal) SL/TP: Configurable in pips Max trades/day: User-defined (default = 99 = unlimited) Manual close: Adjustable by time Entry type: Market (not limit) Visuals: Plotshape triangle for BUY entry 👨‍💻 Credits: 💡 Developed by: LANZ 🧠 Strategy logic & execution: LANZ ✅ Designed for: Clean backtesting, clarity in execution, and intraday logic simulation
Pine Script®策略
由rau_u_lanz提供
Pullback Pro Dow Strategy v7 (ADX Filter) ### **Strategy Description (For TradingView)** #### **Title:** Pullback Pro: Dow Theory & ADX Strategy --- #### **1. Summary** This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities. To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum. --- #### **2. Core Logic: How It Works** The strategy's logic is broken down into three main steps: **Step 1: Trend Determination (Dow Theory)** * The primary trend is identified by analyzing recent pivot points. * An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL). * A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL). * If neither pattern is present, the strategy considers the market to be in a range and will not seek trades. **Step 2: Entry Signal (Pullback to EMA)** * Once a clear trend is established, the strategy waits for a price correction. * **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA. * **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA. **Step 3: Confirmation & Risk Management** * **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets. * **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point: * For long trades, it's placed at the `lastPivotLow`. * For short trades, it's placed at the `lastPivotHigh`. * **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2). --- #### **3. Input Settings Explained** **① Dow Theory Settings** * **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots. **② Entry Logic (Pullback)** * **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries. **③ Risk & Exit Management** * **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target. * **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit. * **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target. **④ Filters** * **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter. * **ADX Length:** The lookback period for the ADX calculation. * **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level. --- #### **4. Best Practices & Recommendations** * This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior. * It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect. * **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application. * Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics. --- #### **DISCLAIMER** This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
Pine Script®策略
由Salaryman_G提供
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.
Pine Script®策略
由Quant_Trading_Pro提供
3
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.
Pine Script®策略
由exlux提供
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.**
Pine Script®策略
由ArganaBridgeCapital提供
7
Canuck Trading Trader StrategyCanuck Trading Trader Strategy Overview The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns. Key Features Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals. Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward. High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission. Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance. Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding). Performance Highlights Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital: Net Profit: $2,279,888.08 (227.99%) Win Rate: 52.94% (3,039 winning trades out of 5,741) Profit Factor: 3.495 Max Drawdown: 2.20% Average Winning Trade: $1,050.91 (0.55%) Average Losing Trade: $338.20 (0.18%) Sharpe Ratio: 2.468 Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing. Usage Instructions Setup: Apply the strategy to a NASDAQ:TSLA 15-minute chart. Ensure your TradingView account supports bar magnification for accurate results. Configuration: Lookback Candles: Default is 2 (recommended). Min Trend Strength: Set to 0.2% for optimal trade frequency. Stop Loss: Default 3.0% to cap losses. Take Profit: Default 2.0% to secure gains. Order Size: 10% of equity per trade. Pyramiding: Allows up to 2 orders. Commission: Set to 0.1. Slippage: Set to 1 tick. Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings. Backtesting: Run backtests over March 1, 2024, to June 20, 2025, to verify performance. Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance. Live Trading: Use with a compatible broker or TradingView alerts for automated execution. Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades). Validate in a demo account before deploying with real capital. Risk Disclosure Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
Pine Script®策略
由ctoincanada提供
4
Long-Leg Doji Breakout StrategyThe Long-Leg Doji Breakout Strategy is a sophisticated technical analysis approach that capitalizes on market psychology and price action patterns. Core Concept: The strategy identifies Long-Leg Doji candlestick patterns, which represent periods of extreme market indecision where buyers and sellers are in equilibrium. These patterns often precede significant price movements as the market resolves this indecision. Pattern Recognition: The algorithm uses strict mathematical criteria to identify authentic Long-Leg Doji patterns. It requires the candle body to be extremely small (≤0.1% of the total range) while having long wicks on both sides (at least 2x the body size). An ATR filter ensures the pattern is significant relative to recent volatility. Trading Logic: Once a Long-Leg Doji is identified, the strategy enters a "waiting mode," monitoring for a breakout above the doji's high (long signal) or below its low (short signal). This confirmation approach reduces false signals by ensuring the market has chosen a direction. Risk Management: The strategy allocates 10% of equity per trade and uses a simple moving average crossover for exits. Visual indicators help traders understand the pattern identification and trade execution process. Psychological Foundation: The strategy exploits the natural market cycle where uncertainty (represented by the doji) gives way to conviction (the breakout), creating high-probability trading opportunities. The strength of this approach lies in its ability to identify moments when market sentiment shifts from confusion to clarity, providing traders with well-defined entry and exit points while maintaining proper risk management protocols. How It Works The strategy operates on a simple yet powerful principle: identify periods of market indecision, then trade the subsequent breakout when the market chooses direction. Step 1: Pattern Detection The algorithm scans for Long-Leg Doji candles, which have three key characteristics: Tiny body (open and close prices nearly equal) Long upper wick (significant rejection of higher prices) Long lower wick (significant rejection of lower prices) Step 2: Confirmation Wait Once a doji is detected, the strategy doesn't immediately trade. Instead, it marks the high and low of that candle and waits for a definitive breakout. Step 3: Trade Execution Long Entry: When price closes above the doji's high Short Entry: When price closes below the doji's low Step 4: Exit Strategy Positions are closed when price crosses back through a 20-period moving average, indicating potential trend reversal. Market Psychology Behind It A Long-Leg Doji represents a battlefield between bulls and bears that ends in a stalemate. The long wicks show that both sides tried to push price in their favor but failed. This creates a coiled spring effect - when one side finally gains control, the move can be explosive as trapped traders rush to exit and momentum traders jump aboard. Key Parameters Doji Body Threshold (0.1%): Ensures the body is truly small relative to the candle's range Wick Ratio (2.0): Both wicks must be at least twice the body size ATR Filter: Uses Average True Range to ensure the pattern is significant in current market conditions Position Size: 10% of equity per trade for balanced risk management Pros: High Probability Setups: Doji patterns at key levels often lead to significant moves as they represent genuine shifts in market sentiment. Clear Rules: Objective criteria for entry and exit eliminate emotional decision-making and provide consistent execution. Risk Management: Built-in position sizing and exit rules help protect capital during losing trades. Market Neutral: Works equally well for long and short positions, adapting to market direction rather than fighting it. Visual Confirmation: The strategy provides clear visual cues, making it easy to understand when patterns are forming and trades are triggered. Cons: False Breakouts: In choppy or ranging markets, price may break the doji levels only to quickly reverse, creating whipsaws. Patience Required: Traders must wait for both pattern formation and breakout confirmation, which can test discipline during active market periods. Simple Exit Logic: The moving average exit may be too simplistic, potentially cutting profits short during strong trends or holding losers too long during reversals. Volatility Dependent: The strategy relies on sufficient volatility to create meaningful doji patterns - it may underperform in extremely quiet markets. Lagging Entries: Waiting for breakout confirmation means missing the very beginning of moves, reducing potential profit margins. Best Market Conditions The strategy performs optimally during periods of moderate volatility when markets are making genuine directional decisions rather than just random noise. It works particularly well around key support/resistance levels where the market's indecision is most meaningful. Optimization Considerations Consider combining with additional confluence factors like volume analysis, support/resistance levels, or other technical indicators to improve signal quality. The exit strategy could also be enhanced with trailing stops or multiple profit targets to better capture extended moves while protecting gains. Best for Index option, Enjoy !!
Pine Script®策略
由kingshukghosh71提供
GStrategy 1000Pepe 15mTrend Following Candlestick Strategy with EMA Filter and Exit Delay Strategy Concept This strategy combines candlestick patterns with EMA trend filtering to identify high-probability trade entries, featuring: Entry Signals: Hammer and Engulfing patterns confirmed by EMA trend Trend Filter: Fast EMA (20) vs Slow EMA (50) crossover system Risk Management: 5% stop-loss + 1% trailing stop Smart Exit: 2-bar delay after exit signals to avoid whipsaws Key Components Trend Identification: Uptrend: Fast EMA > Slow EMA AND rising Downtrend: Fast EMA < Slow EMA AND falling Entry Conditions: pinescript // Bullish Entry (Long) longCondition = (Hammer OR Bullish Engulfing) AND Uptrend AND no existing position // Bearish Entry (Short) shortCondition = Bearish Engulfing AND Downtrend AND no existing position Exit Mechanics: Primary Exit: EMA crossover (Fast crosses Slow) Delayed Execution: Waits 2 full candles after signal Emergency Exits: 5% fixed stop-loss 1% trailing stop Visual Dashboard: Colored EMA lines (Blue=Fast, Red=Slow) Annotated candlestick patterns Background highlighting for signals Distinct markers for entries/exits Unique Features Pattern Recognition: Enhanced Hammer detection (strict body/wick ratios) Multi-candle engulfing confirmation Trend-Confirmation: Requires price and EMA alignment Filters counter-trend patterns Exit Optimization: pinescript // Delay implementation if exit_signal_triggered counter := 2 // Start countdown else if counter > 0 counter -= 1 // Decrement each bar exit_trade = (counter == 1) // Execute on final bar Risk Parameters Parameter Value Description Stop Loss 5% Fixed risk per trade Trailing Stop 1% Locks in profits Exit Delay 2 bars Reduces false exits Position Size 100% No pyramiding Visualization Examples 🟢 Green Triangle: Bullish entry 🔴 Red Triangle: Bearish entry ⬇️ Blue X: Long exit (after delay) ⬆️ Green X: Short exit (after delay) 🎯 Pattern Labels: Identifies hammer/engulfing Recommended Use Timeframes: 1H-4H (reduces noise) Markets: Trend-prone assets (FX, indices) Best Conditions: Strong trending markets Avoid: Choppy/Ranging markets
Pine Script®策略
由Graali提供
2
Supply/Demand Zones + Engulfment-based ExecutionSupply/Demand Zones + Engulfment-Based Execution Strategy Overview This strategy combines institutional trading concepts—supply/demand zones and engulfing candle patterns—to generate high-probability long and short trade setups. The system uses aggregated price action to identify potential reversal zones and confirms entries with engulfing candle patterns, ensuring trades are only taken when market structure shows commitment in the direction of the trade. Core Concepts • Supply & Demand Zones: These are automatically detected by analyzing aggregated bullish and bearish candle structures over user-defined intervals. Supply zones are formed after bearish continuation patterns; demand zones appear after bullish continuation patterns. • Engulfing Entries: Once price enters a zone, the strategy waits for a bullish engulfing pattern (in a demand zone) or a bearish engulfing pattern (in a supply zone) before executing a trade. This adds confirmation and reduces false signals. • Risk Management: Stop-loss is placed at the low (for long trades) or high (for short trades) of the engulfed candle. Take-profit can be calculated using a fixed R-multiple (risk-to-reward ratio) or a user-defined target price. Key Features Fully customizable aggregation factor for zone detection Visual zone boxes, entry/SL/TP boxes, and engulfing pattern labels Optional removal of mitigated zones for cleaner charting Configurable trade mode (Long only, Short only, or Both) Support for trading sessions and date filtering Alerts for price entering supply or demand zones How to Use Select Aggregation Factor: Choose how many candles to group together for identifying key zones (e.g., 4x timeframe). Enable Zones: Turn on supply and/or demand zones as needed. Set Execution Parameters: – Choose R-multiple (e.g., 2:1 risk-reward) – Or use a fixed take-profit price Define Trade Time Window: – Set the date and time ranges to restrict execution – Use Start Hour and End Hour to limit trades to specific sessions (e.g., London/New York) Run on Desired Timeframe: Typically used on 15m–4H charts, depending on your strategy and the asset’s volatility. Ideal For • Traders using Smart Money Concepts (SMC) • Those who value high-confluence entries • Intraday to swing traders looking for structure-based automation ⚠️ Important Notes • The strategy requires engulfing confirmation within the zone to enter a position. • This script does not repaint and executes trades on a bar close basis. • Backtest results may vary based on session filters and aggregation factor. © Attribution This strategy was developed by The_Forex_Steward and is licensed under the Mozilla Public License 2.0. You are free to use, modify, and distribute it under the terms of that license.
Pine Script®策略
由The_Forex_Steward提供