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Volume Weighted SuperTrend | QuantumResearch

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QuantumResearch Volume Weighted Supertrend (VWST)

The Volume Adaptive Supertrend (VWST) is a dynamic trend-following tool that enhances traditional Supertrend calculations by incorporating volume-weighted market conditions.

This indicator adapts its trend signals based on volume-adjusted price action, allowing traders to refine their entries and exits with improved responsiveness. 🚀📊

1. Key Features

  • Volume-Weighted Adaptation: Uses various moving averages (VWMA, EMA, SMA, etc.) to adjust ATR bands based on market activity.
  • Customizable Trend Sensitivity: Adjusts ATR multipliers separately for bullish and bearish conditions.
  • Adaptive Supertrend Calculation: Dynamically recalculates trend direction based on volume-enhanced price movements.
  • Multi-Timeframe Compatibility: Can be applied across different assets and timeframes for versatile market analysis.
  • Visual Clarity & Alerts: Color-coded trend signals, shaded areas, and real-time alerts for trend shifts.


2. How It Works

A. Volume-Weighted Price Calculation
  • The indicator applies a user-selected moving average (EMA, VWMA, SMA, etc.) to price and volume data
  • This ensures that trend calculations are more reactive to strong volume surges and less influenced by low-liquidity fluctuations.


B. Adaptive ATR-Based Trend Filtering
  • ATR bands are dynamically adjusted based on volume-weighted price action.
  • Separate ATR multipliers for bullish and bearish conditions allow for refined sensitivity control.
  • The Supertrend line shifts dynamically to reflect these conditions.


C. Signal Generation
  • Bullish Trend: The price closes above the adaptive Supertrend line. ✅
  • Bearish Trend: The price closes below the adaptive Supertrend line. ❌
  • Long Entry: Triggered when trend direction switches from bearish to bullish.
  • Short Entry: Triggered when trend direction switches from bullish to bearish.


3. Visual Representation

A. Color-Coded Trend Signals
  • Green Trend Line: Indicates a bullish trend.
  • Red Trend Line: Indicates a bearish trend.
  • Gray Trend Line: Neutral phase.


B. Dynamic Background Fill
  • Shaded Green Areas: Confirmed uptrend zones.
  • Shaded Red Areas: Confirmed downtrend zones.


4. Customization & Parameters

  • ATR Length & Multipliers: Adjust trend sensitivity with separate multipliers for bullish and bearish phases.
  • Moving Average Type: Select from VWMA, EMA, SMA, HMA, WMA, DEMA, TEMA for volume-weighted calculations.
  • Volume Length: Modify how far back volume data is used to refine trend calculations.
  • Color Themes: Choose from 8 distinct color modes for clear visual representation.


5. Backtest & Market Applications

Backtest Summary:
The Volume Adaptive Supertrend (VWST) has been tested across multiple assets, including:
  • BTC/USD
    snapshot
  • ETH/USD
    snapshot
  • SOL/USD
    snapshot


📊 Key Observations:
  • Responsive Trend Detection: The volume-weighted adaptation helps minimize lag in trend shifts.
  • Versatile Across Market Conditions: Works well in both trending and consolidating phases with appropriate settings.
  • Customizable Risk Control: ATR multipliers can be adjusted to fine-tune signal sensitivity.


⚠️ Disclaimer: This indicator is designed to complement existing analysis techniques. Market conditions vary, and no tool can guarantee future performance. Always use proper risk management when trading.

6. Final Thoughts

  • The Volume Weighted Supertrend (VWST) enhances traditional Supertrend indicators by incorporating volume-adjusted trend detection.
  • Its dynamic ATR-based trend filtering ensures greater responsiveness to real market conditions.
  • Suitable for trend traders, breakout traders, and risk-conscious investors looking for volume-driven confirmations.
  • Use it alongside other confluences to build a robust trading system.
  • Important Reminder: No single indicator guarantees profitability. Always validate signals with additional market context. 📊

Informacje o Wersji
Added the Switch button for the timeframe.

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