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Indikatoren und Strategien

SuperTrend Strategy with Trend-Based Exits🟩 SuperTrend Strategy with Trend-Based Exits This is a fully automated trend-following strategy based on the popular SuperTrend indicator, enhanced with a position sizing algorithm tied to stop-loss distance and dynamic entry/exit rules. The strategy is designed for futures trading with an emphasis on sustainable risk, realistic backtesting, and transparent logic. 🧠 Concept and Methodology The strategy uses the SuperTrend indicator, which is derived from ATR (Average True Range) and is widely used to capture medium- to long-term market trends. Key features: ✅ Entries are triggered only when the SuperTrend direction changes (trend reversal). ✅ Exits are performed using a dynamic stop-loss placed at the SuperTrend line. ✅ Position size is automatically calculated based on the trader’s fixed dollar risk per trade and the current distance to the stop-loss. ✅ Rounding logic is included to ensure quantity is valid for the exchange’s lot size. This strategy does not use any take-profit or classic trailing stop — the position is only closed when the trend reverses or the stop is hit by touching the SuperTrend line. ⚙️ Default Parameters ATR Length: 300 Factor: 7.5 Risk per trade: $90 (3% of the default $3,000 capital) Lot step: 10 Commission: 0.05% These default parameters are not universal. They were optimized specifically for STXUSDT swap at 15M timeframe at Bybit and may not produce viable results on other pairs and timeframes. Users are encouraged to customize the settings according to specific asset’s volatility, timeframe and other characteristics. ❗ These default settings yield meaningful backtesting results on STXUSDT with a reasonable number of trades (105+) over 7-month period. If applied to other assets, results may vary significantly. 📈 Position Sizing Logic The strategy uses a dynamic position sizing formula: Pine Script® position_size = floor((risk_per_trade / stop_loss_distance) / lot_step) * lot_step This ensures the trader always risks a fixed dollar amount per trade and never exceeds a sustainable equity exposure (recommended 2% or less). ✅ Realism in Backtesting To ensure realistic and non-misleading backtest results, this strategy includes: — Slippage and commission settings matching average exchange conditions (commission = 0.05%, slippage 5 ticks). — Position sizing based on stop-loss distance (not fixed contract quantity).* — A fixed risk-per-trade model that adheres to responsible capital management principles. — This is in compliance with TradingView's Script publishing rules and House Rules. 📌 How to Use Apply the strategy to a clean chart (preferably 15M for STXUSDT by default). If using another asset, adjust: - ATR Length - Factor - Risk per trade - Qty step (lot precision for the symbol) Avoid using with other indicators unless you understand their purpose. Use the Strategy Tester to evaluate performance and optimize parameters. ⚠️ Disclaimer This is not financial advice. Always perform forward testing and assess risk before deploying any strategy on live capital. The strategy is designed for educational and experimental use.
Pine Script® Strategie
von nefyodov.artyom
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® Strategie
von EfeErdost
0-5 Box Strategy Tester v4🟩 0-5 Box Strategy Tester v4 — Explained Simply This script is a modular hourly breakout strategy designed to help traders test and trade breakouts (or pullbacks) from the first 5-minute range of any selected hour. It supports both long and short positions and is optimized for scalping or intraday strategies. 🔑 Core Strategy Logic Box Formation: At the start of every hour, the script tracks the high and low of the first 5 minutes (e.g., from 9:00 to 9:04). Trade Trigger: Once price breaks out above or below this 5-minute box (either instantly or after a pullback), it can trigger a long or short entry depending on your settings. Entry Type: Supports two main styles: Breakout entry: Buy/sell as soon as price breaks the box. Pullback re-entry: Wait for price to break the box, pull back, then re-enter on a limit order. 🧪 Smart Entry Filters (Optional but Powerful) You can refine your trades using several filters: ✅ Previous Hour Direction – Only trade in the direction of the last hour’s candle (bullish/bearish). 🔄 Reversal Filter – Only trade against the previous hour’s direction. 💧 Liquidity Sweep – Require the previous hour’s high or low to be swept first (liquidity-based entry). 🔁 Q2 Confirmation (15–30 min logic) – Confirm price action in the second quarter of the hour (like retests or wick-based logic). 🕒 Max Entry Time – Prevent late trades within the hour (e.g., no entries after minute 45). 📦 Max Range % – Avoid trading during overly volatile hours by filtering out wide boxes. 🕘 Flexible Hour Selection You can choose to: Trade all hours Or select specific hours manually (like 4AM, 9AM, etc.) 📉 Risk & Position Sizing Options Supports stop-loss and take-profit by: Points Percentage Risk:Reward Ratio Choose fixed contract size or auto-size based on dollar risk. 📊 Built-In Analytics The strategy tracks and displays: Win rate PnL (total, by hour, by day) Average drawdown Risk metrics (Expectancy, Profit Factor, Payoff Ratio) Hour-by-hour stats (how each hour performs historically) Day-of-week performance Visual tables on chart for easy analysis 🧠 Use Cases This strategy is ideal for: Futures traders (like NQ/ES/GC) who trade specific sessions (e.g., NY open, London) Scalpers looking for tight breakouts or pullbacks Systematic traders backtesting precision setups Traders using confluence like session breaks, liquidity sweeps, and inside-hour confirmations
Pine Script® Strategie
von mickey1984
Reversal & Breakout Strategy - CompleteThis is a complete intraday trading strategy script for TradingView that lets you: 1. Choose Between Two Styles of Trades: Reversals: It looks for large bullish or bearish candles during market sessions and enters trades expecting price to reverse. Breakouts: It scans for price breaking above or below a recent high or low (based on a lookback range) and enters in the direction of the breakout. 2. Filters Trades by Session and Day Type: Trades only during sessions you choose: NY1, NY2, London, Asia, etc. Trades only on specific day types (e.g., DNP, DWP, Range 1, Range 2), as classified by a custom daily behavior model. 3. Uses 9:30 AM Candle Logic (ORB): Captures the 9:30 AM Eastern candle's high/low using 1-minute data. Allows breakout confirmation using this range. 4. Entry + Exit Logic: Enters on reversal or breakout confirmation. Automatically places stop-loss and take-profit orders (based on your input, in ticks or points). Can require classification before entry (e.g., don’t trade until the market type is known). 5. Tracks Trades and Performance: Records each trade's PnL, drawdown, win/loss, classification, time, and session. Displays a table with analytics like win rate, expectancy, average drawdown, trade distribution by day/classification. 6. Visually Shows All Trades: Draws arrows and shapes when trades are triggered. Labels when trades are blocked (e.g., if not classified yet). Plots breakout levels and 9:30 AM box.
Pine Script® Strategie
von mickey1984
Fisher Crossover StrategyThe Fisher Crossover Strategy is a popular technical trading method that uses the Fisher Transform indicator developed by John Ehlers. This indicator mathematically converts price data into a normal Gaussian distribution, making market turning points sharper and easier to identify. The strategy is based on two lines: the Fisher line, which is the main transformed price value, and the Trigger line, which is a one-period lag of the Fisher line. Traders use the crossover of these lines to determine buy and sell opportunities. A buy signal is generated when the Fisher line crosses above the Trigger line, indicating that bullish momentum may be starting, while a sell signal occurs when the Fisher line crosses below the Trigger line, suggesting a possible bearish reversal. Signals that occur relative to the zero line are often considered stronger; for example, a buy signal below the zero line may indicate a deeper market reversal. The strategy is simple to follow and can be applied to various markets including stocks, forex, commodities, and cryptocurrencies. However, like all crossover strategies, it can produce false signals during sideways or ranging markets. To reduce whipsaws, traders often combine the Fisher Crossover Strategy with other tools such as support and resistance levels, volume analysis, or moving averages. Proper risk management with stop-loss and take-profit levels is also essential. Overall, the Fisher Crossover Strategy is valued for its clear entry and exit rules and its ability to highlight potential market reversals earlier than many other indicators.
Pine Script® Strategie
von kamalverma1207
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® Strategie
von mnwrahmad
Ultimate Scalping Strategy v2Strategy Overview This is a versatile scalping strategy designed primarily for low timeframes (like 1-min, 3-min, or 5-min charts). Its core logic is based on a classic EMA (Exponential Moving Average) crossover system, which is then filtered by the VWAP (Volume-Weighted Average Price) to confirm the trade's direction in alignment with the market's current intraday sentiment. The strategy is highly customizable, allowing traders to add layers of confirmation, control trade direction, and manage exits with precision. Core Strategy Logic The strategy's entry signals are generated when two primary conditions are met simultaneously: Momentum Shift (EMA Crossover): It looks for a crossover between a fast EMA (default length 9) and a slow EMA (default length 21). Buy Signal: The fast EMA crosses above the slow EMA, indicating a potential shift to bullish momentum. Sell Signal: The fast EMA crosses below the slow EMA, indicating a potential shift to bearish momentum. Trend/Sentiment Filter (VWAP): The crossover signal is only considered valid if the price is on the "correct" side of the VWAP. For a Buy Signal: The price must be trading above the VWAP. This confirms that, on average, buyers are in control for the day. For a Sell Signal: The price must be trading below the VWAP. This confirms that sellers are generally in control. Confirmation Filters (Optional) To increase the reliability of the signals and reduce false entries, the strategy includes two optional confirmation filters: Price Action Filter (Engulfing Candle): If enabled (Use Price Action), the entry signal is only valid if the crossover candle is also an "engulfing" candle. A Bullish Engulfing candle is a large green candle that completely "engulfs" the body of the previous smaller red candle, signaling strong buying pressure. A Bearish Engulfing candle is a large red candle that engulfs the previous smaller green candle, signaling strong selling pressure. Volume Filter (Volume Spike): If enabled (Use Volume Confirmation), the entry signal must be accompanied by a surge in volume. This is confirmed if the volume of the entry candle is greater than its recent moving average (default 20 periods). This ensures the move has strong participation behind it. Exit Strategy A position can be closed in one of three ways, creating a comprehensive exit plan: Stop Loss (SL): A fixed stop loss is set at a level determined by a multiple of the Average True Range (ATR). For example, a 1.5 multiplier places the stop 1.5 times the current ATR value away from the entry price. This makes the stop dynamic, adapting to market volatility. Take Profit (TP): A fixed take profit is also set using an ATR multiplier. By setting the TP multiplier higher than the SL multiplier (e.g., 2.0 for TP vs. 1.5 for SL), the strategy aims for a positive risk-to-reward ratio on each trade. Exit on Opposite Signal (Reversal): If enabled, an open position will be closed automatically if a valid entry signal in the opposite direction appears. For example, if you are in a long trade and a valid short signal occurs, the strategy will exit the long position immediately. This feature turns the strategy into more of a reversal system. Key Features & Customization Trade Direction Control: You can enable or disable long and short trades independently using the Allow Longs and Allow Shorts toggles. This is useful for trading in harmony with a higher-timeframe trend (e.g., only allowing longs in a bull market). Visual Plots: The strategy plots the Fast EMA, Slow EMA, and VWAP on the chart for easy visualization of the setup. It also plots up/down arrows to mark where valid buy and sell signals occurred. Dynamic SL/TP Line Plotting: A standout feature is that the strategy automatically draws the exact Stop Loss and Take Profit price lines on the chart for every active trade. These lines appear when a trade is entered and disappear as soon as it is closed, providing a clear visual of your risk and reward targets. Alerts: The script includes built-in alertcondition calls. This allows you to create alerts in TradingView that can notify you on your phone or execute trades automatically via a webhook when a long or short signal is generated.
Pine Script® Strategie
von sebamarghella
3
Bollinger Bands SMA 20_2 StrategyMean reversion strategy using Bollinger Bands (20-period SMA with 2.0 standard deviation bands). Trade Triggers: 🟢 BUY SIGNAL: When: Price crosses above the lower Bollinger Band Logic: Price has hit oversold territory and is bouncing back Action: Places a long position with stop at the lower band 🔴 SELL SIGNAL: When: Price crosses below the upper Bollinger Band Logic: Price has hit overbought territory and is pulling back Action: Places a short position with stop at the upper band
Pine Script® Strategie
von meowBTC
1
ICT OTE Strategy Crypto PublicICT OTE Strategy Crypto Public This strategy automates a classic ICT (Inner Circle Trader) setup specifically tailored for the high-volatility nature of cryptocurrency markets. It aims to enter a trade on a retracement after a confirmed Break of Structure (BOS), using a dual-swing detection method to validate the market's direction before looking for an entry. The entire process is automated, from identifying the market structure to managing the trade with advanced risk management options. This version uses a percentage of equity for its order sizing, which is ideal for crypto trading. How It Works Dual Swing Detection: The strategy uses two different sets of swing strengths to analyze market structure for higher accuracy: Entry Swings: Weaker, more sensitive swings used to define the immediate dealing range for a potential trade. Validator Swings: Stronger, more significant swings used to confirm a true Break of Structure. Break of Structure (BOS): A trade setup is only considered valid after a strong "Validator" swing breaks through a previous "Entry" swing. This confirms the market's intended direction and filters out weak or false moves. Identify Retracement Leg: After a confirmed BOS, the strategy identifies the most recent "Entry Swing" price leg that led to the break. Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0). Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.618), anticipating a price pullback into a discount or premium array. After a bullish BOS, it looks to BUY the retracement. After a bearish BOS, it looks to SELL the retracement. Risk Management: Stop Loss is placed at the start of the leg (the 1.0 level). Take Profit is placed at a user-defined level (defaulting to the 0.0 level, with extension options). Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit. How to Use Asset Selection: This strategy is designed for cryptocurrency markets. Its use of percentage-based order sizing is not suitable for tick-based markets like futures. Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups. Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Swing Sensitivity" to find the best settings for your specific market and timeframe.
Pine Script® Strategie
von DropkingICT
Fusion Trend Pulse V2SCRIPT TITLE Adaptive Fusion Trend Pulse V2 - Multi-Regime Strategy DETAILED DESCRIPTION FOR PUBLICATION 🚀 INNOVATION SUMMARY The Adaptive Fusion Trend Pulse V2 represents a breakthrough in algorithmic trading by introducing real-time market regime detection that automatically adapts strategy parameters based on current market conditions. Unlike static indicator combinations, this system dynamically adjusts its behavior across trending, choppy, and volatile market environments, providing a sophisticated multi-layered approach to market analysis. 🎯 CORE INNOVATIONS JUSTIFYING PROTECTED STATUS 1. Adaptive Market Regime Engine Trending Market Detection: Uses ADX >25 with directional movement analysis Volatile Market Classification: ATR-based volatility regime scoring (>1.2 threshold) Choppy Market Identification: ADX <20 combined with volatility patterns Dynamic Parameter Adjustment: All thresholds adapt based on detected regime 2. Multi-Component Fusion Algorithm McGinley Dynamic Trend Baseline: Self-adjusting moving average that adapts to price velocity Adaptive RMI (Relative Momentum Index): Enhanced RSI with momentum period adaptation Zero-Lag EMA Smoothed CCI: Custom implementation reducing lag while maintaining signal quality Hull MA Gradient Analysis: Slope strength normalized by ATR for trend confirmation Volume Spike Detection: Regime-adjusted volume confirmation (0.8x-1.3x multipliers) 3. Intelligence Layer Features Cooldown System: Prevents overtrading with regime-specific waiting periods (1-3 bars) Performance Tracking: Real-time adaptation based on recent trade outcomes Multi-Exchange Alert Integration: JSON-formatted alerts for automated trading Comprehensive Dashboard: 16-metric real-time performance monitoring 📊 TECHNICAL SPECIFICATIONS Market Regime Detection Philosophy: The system continuously monitors market structure through volatility analysis and directional strength measurements. Rather than applying fixed thresholds, it creates dynamic response profiles that adjust the strategy's sensitivity, timing, and filtering based on the current market environment. Adaptive Parameter Concept: All strategy components modify their behavior based on regime classification. Volume requirements become more or less stringent, momentum thresholds shift to match market character, and exit timing adjusts to prevent whipsaws in different market conditions. Entry Conditions (Both Long/Short): McGinley trend alignment (close vs trend line) Hull MA slope confirmation with ATR-normalized strength Adaptive CCI above/below regime-specific thresholds RMI momentum confirmation (>50 for long, <50 for short) Volume spike exceeding regime-adjusted threshold Regime-specific additional filters Exit Strategy: Dual take-profit system (2% and 4% default, customizable) Momentum weakness detection (CCI reversal) Trend breakdown (close below/above McGinley line) Regime-specific urgency multipliers for faster exits in choppy markets 🎛️ USER CUSTOMIZATION OPTIONS Core Parameters: RMI Length & Momentum periods CCI smoothing length McGinley Dynamic length Hull MA period for gradient analysis Volume spike detection (length & multiplier) Take profit levels (separate for long/short) Adaptive Settings: Market regime detection period (21 bars default) Adaptation period for performance tracking (60 bars) Volatility adaptation toggle Trend strength filtering toggle Momentum sensitivity multiplier (0.5-2.0 range) Dashboard & Alerts: Dashboard position (4 corners) Dashboard size (Small/Normal/Large) Transparency settings (0-100%) Custom alert messages for bot integration Date range filtering 🏆 UNIQUE VALUE PROPOSITIONS 1. Market Intelligence: First Pine Script strategy to implement comprehensive regime detection with parameter adaptation - most strategies use static settings regardless of market conditions. 2. Fusion Methodology: Combines 5+ distinct technical approaches (trend-following, momentum, volatility, volume, regime analysis) in a cohesive adaptive framework rather than simple indicator stacking. 3. Performance Optimization: Built-in learning system tracks recent performance and adjusts sensitivity - providing evolution rather than static rule-following. 4. Professional Integration: Enterprise-ready with JSON alert formatting, multi-exchange compatibility, and comprehensive performance tracking suitable for institutional use. 5. Visual Intelligence: Advanced dashboard provides 16 real-time metrics including regime classification, signal strength, and performance analytics - far beyond basic P&L displays. 🔧 TECHNICAL IMPLEMENTATION HIGHLIGHTS Primary Applications: Swing Trading: 4H-1D timeframes with regime-adapted entries Algorithmic Trading: Automated execution via webhook alerts Portfolio Management: Multi-timeframe analysis across different market conditions Risk Management: Regime-aware position sizing and exit timing Target Markets: Cryptocurrency pairs (high volatility adaptation) Forex majors (trending market optimization) Stock indices (choppy market handling) Commodities (volatile regime management) 🎯 WHY THIS ISN'T JUST AN INDICATOR MASHUP Integrated Adaptation Framework: Unlike scripts that simply combine multiple indicators with static settings, this system creates a unified intelligence layer where each component influences and adapts to the others. The McGinley trend baseline doesn't just provide signals - it dynamically adjusts its sensitivity based on market regime detection. The momentum components modify their thresholds based on trend strength analysis. Feedback Loop Architecture: The strategy incorporates a closed-loop learning system where recent performance influences future parameter selection. This creates evolution rather than static rule application. Most indicator combinations lack this adaptive learning capability. Contextual Decision Making: Rather than treating each signal independently, the system uses contextual analysis where the same technical setup may generate different responses based on the current market regime. A momentum signal in a trending market triggers different behavior than the identical signal in choppy conditions. Unified Risk Management: The regime detection doesn't just affect entries - it creates a comprehensive risk framework that adjusts exit timing, cooldown periods, and position management based on market character. This holistic approach distinguishes it from simple indicator stacking. Custom Implementation Depth: Each component uses proprietary implementations (custom McGinley calculation, zero-lag CCI smoothing, enhanced RMI) rather than standard built-in functions, creating a cohesive algorithmic ecosystem rather than disconnected indicator outputs. Custom Functions: mcginley(): Proprietary implementation of McGinley Dynamic MA rmi(): Enhanced Relative Momentum Index with custom parameters zlema(): Zero-lag EMA for CCI smoothing Regime classification algorithms with multi-factor analysis Performance Optimizations: Efficient variable management with proper scoping Minimal repainting through careful historical referencing Optimized calculations to prevent timeout issues Memory-efficient tracking systems Alert System: JSON-formatted messages for API integration Dynamic symbol/exchange substitution Separate entry/exit/TP alert conditions Customizable message formatting ⚡ WHY THIS REQUIRES PROTECTION This strategy represents months of research into adaptive trading systems and market regime analysis. The specific combination of: Proprietary regime detection algorithms Custom adaptive parameter calculations Multi-indicator fusion methodology Performance-based learning system Professional-grade implementation Creates intellectual property that provides genuine competitive advantage. The methodology is not available in existing open-source scripts and represents original research into algorithmic trading adaptation. 🎯 EDUCATIONAL VALUE Users gain exposure to: Advanced market regime analysis techniques Adaptive parameter optimization concepts Multi-timeframe indicator fusion Professional strategy development practices Automated trading integration methods The comprehensive dashboard and parameter explanations serve as a learning tool for understanding how professional algorithms adapt to changing market conditions. CATEGORY SELECTION Primary: Strategy Secondary: Trend Analysis SUGGESTED TAGS adaptive, trend, momentum, regime, strategy, alerts, dashboard, mcginley, rmi, cci, professional MANDATORY DISCLAIMER Disclaimer: This strategy is for educational and informational purposes only. It does not constitute financial advice. Trading cryptocurrencies involves substantial risk, and past performance is not indicative of future results. Always backtest and forward-test before using on a live account. Use at your own risk.
Pine Script® Strategie
von robertgroff72
Brain Premium [ALGO]💡 Brain Premium ALGO Brainpremium ALGO is a strategy algorithm that analyzes a two-phase regional liquidity structure and only opens positions on price breakouts occurring within these liquidity zones. This system is developed based on the market experience of manual traders and automatically executes trade decisions using AI-like rules and specific triggers. 💡 Two-Phase Liquidity-Based Entry Strategy This strategy operates by detecting liquidity sweep zones and confirmed reversal signals: 🔹 Phase 1 – Liquidity Sweep: Price is expected to sweep areas where equal highs/lows or liquidity clusters exist. These zones are considered potential reversal levels. 🔹 Phase 2 – Confirmed Entry: After liquidity is swept, entries are triggered only by confirmed reversal signals such as structural breaks, inside bars, or breakouts in the opposite direction. ✅ Entries are triggered only when liquidity and reversal confirmation occur simultaneously. 🎯 This approach targets high-probability, low-risk trades. ⚙️ Key Features 🔍 Dynamic Liquidity Detection — Automatically identifies liquidity zones. 🧩 Modular Entry Options (1–2–3) — Allows opening positions via different strategy paths. 🛡️ Dynamic Stop Loss System — Stop Loss adjusts as price moves favorably. 📈 Advanced Risk Management — Adjustable Take Profit, Stop Loss, leverage, balance, and mode. 🔔 JSON Alert Support — Connects to platforms like BingX via webhook. 🧾 Information Panel — Displays real-time trade data and strategy status. 📊 Backtest & Default Settings Strategy tests are conducted with realistic and sustainable parameters: Parameter Value Trading Balance: $100 (%10 of total wallet) Leverage: 10x Stop Loss: 1% Take Profit Type : High TP (optional: Low and Risky also available) Entry Option 1 (optional: 2 and 3 also available) Mode: NORMAL Commission 0.05% Dynamic Stop Loss: Enabled Timeframe: 5 minute Pair ETH/USDT Duration: 30 days 🧭 Usage Instructions Add Brain Premium ALGO to your TradingView chart. Set position size, leverage, and SL/TP levels from the settings panel. Select entry option (1, 2, or 3). Activate backtesting and alert systems to monitor the strategy. ⚠️ Disclaimer This strategy is not financial advice. Past performance does not guarantee future results. Trade only with capital you can afford to risk and always test thoroughly in a demo environment first.
Pine Script® Strategie
von WhiteRabbitt
ICT OTE Strategy Futures PublicICT OTE Strategy This strategy automates a classic ICT (Inner Circle Trader) setup that aims to enter a trade on a retracement after a confirmed Break of Structure (BOS). It is designed to identify high-probability setups by waiting for the market to show its hand before looking for an entry within a "discount" or "premium" array. The entire process is automated, from identifying the market structure to managing the trade with a dynamic stop loss. How It Works Break of Structure (BOS): The strategy first waits for a strong, validated swing to break a previous, weaker swing high or low. This confirms the market's intended direction. Identify Retracement Leg: After a BOS, the strategy identifies the most recent price leg that led to the break. Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0). Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.508), anticipating a price pullback. After a bullish BOS, it looks to BUY the retracement. After a bearish BOS, it looks to SELL the retracement. Risk Management: Stop Loss is placed at the start of the leg (the 1.0 level). Take Profit is placed at a user-defined level (defaulting to the 0.0 level). Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit. How to Use Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups. Session Filter: Use the "Trading Sessions" filter to align the strategy with ICT's "killzone" concept, ensuring trades are only taken during high-volume periods like the New York session. Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Min Trade Range" to find the best settings for your specific market and timeframe.
Pine Script® Strategie
von DropkingICT