Simple VWMA Smooth | QuantEdgeB

Simple VWMA Smooth (SVS) | QuantEdgeB

🔍 What Is Simple VWMA Smooth?
SVS is a smoothed, volume-aware trend filter that blends a Gaussian-pre-filtered, low-lag moving average with dynamic standard-deviation bands. It identifies trends by measuring when price moves decisively above or below a VWMA (Volume-Weighted Moving Average) baseline—filtering out noise while letting high-volume moves carry more influence than low-volume noise.

⚙️ Core Components
1) DEMA Pre-Filter
A double-EMA smoothing step to reduce initial noise before further processing.
2) Gaussian Smoothing
Applies a small-kernel Gaussian filter to produce a cleaner input series that suppresses rapid spikes.
3) VWMA Baseline (Volume-Weighted Average)
Computes a moving average where each bar is weighted by volume, so the baseline tracks “meaningful” price moves more than low-liquidity fluctuations.
• In high volume → the baseline reacts more to those candles
• In low volume → price changes have less impact
4) Volatility Bands
Surrounds the VWMA line with ± N × SD bands (separate multipliers for upper and lower) to capture current market volatility, creating dynamic thresholds for trend detection.
5) Trend Signal
• Long when price closes above the upper band
• Short when price closes below the lower band
• Otherwise neutral

💡 Why It’s Special
• Volume-Validated Responsiveness: VWMA prioritizes moves backed by volume, helping reduce signals caused by thin-market noise.
• Multi-Stage Filtering: The DEMA → Gaussian → VWMA sequence suppresses noise while keeping trend structure clear.
• Asymmetric Bands: Separate multipliers for upper/lower bands let you tune bullish vs bearish sensitivity independently.
• Visual Clarity: Color-coded candles and filled bands highlight trending phases at a glance, while backtest tables quantify performance.

📊 Backtest Mode
SVS includes an optional backtest table, enabling traders to assess historical effectiveness before using it live.
Backtest Metrics Displayed:
• Equity Max Drawdown
• Profit Factor
• Sharpe Ratio
• Sortino Ratio
• Omega Ratio
• Half Kelly
• Total Trades & Win Rate

💼 Ideal Use Cases
• Trend Identification: Spot cleaner trend starts/exits across stocks, FX, or crypto with reduced lag and fewer false breakouts.
• Volume Regimes: Helps distinguish “real” moves (high participation) from weak moves (low participation).
• Multitimeframe Alignment: Confirm direction across timeframes before entries.
• System Building Block: Use as a volume-aware filter inside broader strategies.

🎨 Default Configuration
• DEMA Length: 7
• Gaussian Kernel: length = 4, sigma = 2.0
• VWMA Length: 14
• Volatility Bands: SD length = 40

📌 In Summary
Simple VWMA Smooth | QuantEdgeB is a volume-weighted, noise-suppressed trend filter that combines DEMA smoothing, Gaussian filtering, a VWMA baseline, and dynamic SD bands to separate genuine directional moves from market noise—across any asset or timeframe.

🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.