OPEN-SOURCE SCRIPT
Neural Adaptive VWAP

Neural Adaptive VWAP with ML Features is an advanced trading indicator that enhances traditional Volume Weighted Average Price (VWAP) calculations through machine learning-inspired adaptive algorithms and predictive volume modeling.
🌟 Key Features:
🧠 Machine Learning-Inspired Adaptation
Dynamic weight adjustment system that learns from prediction errors
Multi-feature volume prediction using time-of-day patterns, price momentum, and volatility
Adaptive learning mechanism that improves accuracy over time
📊 Enhanced VWAP Calculation
Combines actual and predicted volume for forward-looking VWAP computation
Session-based reset with proper daily anchoring
Confidence bands based on rolling standard deviation for dynamic support/resistance
🎯 Advanced Signal Generation
Volume-confirmed crossover signals to reduce false entries
Color-coded candle visualization based on VWAP position
Multi-level strength indicators (strong/weak bullish/bearish zones)
⚙️ Intelligent Feature Engineering
Normalized volume analysis with statistical z-score
Time-series pattern recognition for intraday volume cycles
Price momentum and volatility integration
Sigmoid activation functions for realistic predictions
📈 How It Works:
The indicator employs a sophisticated feature engineering approach that extracts meaningful patterns from:
Volume Patterns: Normalized volume analysis and historical comparisons
Temporal Features: Time-of-day and minute-based cyclical patterns
Market Dynamics: Price momentum, volatility, and rate of change
Adaptive Learning: Error-based weight adjustment similar to neural network training
Unlike static VWAP indicators, this system continuously adapts its calculation methodology based on real-time market feedback, making it more responsive to changing market conditions while maintaining the reliability of traditional VWAP analysis.
🔧 Customizable Parameters:
VWAP Length (1-200 bars)
Volume Pattern Lookback (5-50 periods)
Learning Rate (0.001-0.1) for adaptation speed
Prediction Horizon (1-10 bars ahead)
Adaptation Period for weight updates
📊 Visual Elements:
Blue Line: Adaptive VWAP with predictive elements
Red/Green Bands: Dynamic confidence zones
Colored Candles: Position-based strength visualization
Signal Arrows: Volume-confirmed entry points
Info Table: Real-time performance metrics and weight distribution
🎯 Best Use Cases:
Intraday Trading: Enhanced execution timing with volume prediction
Institutional-Style Execution: Improved VWAP-based order placement
Trend Following: Adaptive trend identification with confidence zones
Support/Resistance Trading: Dynamic levels that adjust to market conditions
🌟 Key Features:
🧠 Machine Learning-Inspired Adaptation
Dynamic weight adjustment system that learns from prediction errors
Multi-feature volume prediction using time-of-day patterns, price momentum, and volatility
Adaptive learning mechanism that improves accuracy over time
📊 Enhanced VWAP Calculation
Combines actual and predicted volume for forward-looking VWAP computation
Session-based reset with proper daily anchoring
Confidence bands based on rolling standard deviation for dynamic support/resistance
🎯 Advanced Signal Generation
Volume-confirmed crossover signals to reduce false entries
Color-coded candle visualization based on VWAP position
Multi-level strength indicators (strong/weak bullish/bearish zones)
⚙️ Intelligent Feature Engineering
Normalized volume analysis with statistical z-score
Time-series pattern recognition for intraday volume cycles
Price momentum and volatility integration
Sigmoid activation functions for realistic predictions
📈 How It Works:
The indicator employs a sophisticated feature engineering approach that extracts meaningful patterns from:
Volume Patterns: Normalized volume analysis and historical comparisons
Temporal Features: Time-of-day and minute-based cyclical patterns
Market Dynamics: Price momentum, volatility, and rate of change
Adaptive Learning: Error-based weight adjustment similar to neural network training
Unlike static VWAP indicators, this system continuously adapts its calculation methodology based on real-time market feedback, making it more responsive to changing market conditions while maintaining the reliability of traditional VWAP analysis.
🔧 Customizable Parameters:
VWAP Length (1-200 bars)
Volume Pattern Lookback (5-50 periods)
Learning Rate (0.001-0.1) for adaptation speed
Prediction Horizon (1-10 bars ahead)
Adaptation Period for weight updates
📊 Visual Elements:
Blue Line: Adaptive VWAP with predictive elements
Red/Green Bands: Dynamic confidence zones
Colored Candles: Position-based strength visualization
Signal Arrows: Volume-confirmed entry points
Info Table: Real-time performance metrics and weight distribution
🎯 Best Use Cases:
Intraday Trading: Enhanced execution timing with volume prediction
Institutional-Style Execution: Improved VWAP-based order placement
Trend Following: Adaptive trend identification with confidence zones
Support/Resistance Trading: Dynamic levels that adjust to market conditions
開源腳本
本著TradingView的真正精神,此腳本的創建者將其開源,以便交易者可以查看和驗證其功能。向作者致敬!雖然您可以免費使用它,但請記住,重新發佈程式碼必須遵守我們的網站規則。
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。
開源腳本
本著TradingView的真正精神,此腳本的創建者將其開源,以便交易者可以查看和驗證其功能。向作者致敬!雖然您可以免費使用它,但請記住,重新發佈程式碼必須遵守我們的網站規則。
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。