Volume SuperTrend AI (Expo)

Category: trend, volume

A hybrid trend indicator that combines a Volume-Weighted SuperTrend with a K-Nearest Neighbors (KNN) classification algorithm to refine trend signals based on historical patterns.

Formula

VWMA = \frac{\sum (Price \times Volume)}{\sum Volume} \\ \text{SuperTrend} = \text{VWMA} \pm (Multiplier \times ATR) \\ \text{KNN Label} = \frac{\sum_{i=1}^k (Weight_i \times Label_i)}{\sum Weight_i} \text{ where } Weight = \frac{1}{Distance + 1e-6}

Inputs

• Neighbors (k) (default: 3)
• Data (n) (default: 10)
• Price Trend (KNN Price Len) (default: 20)
• Prediction Trend (KNN ST Len) (default: 100)
• SuperTrend Length (default: 10)
• SuperTrend Factor (default: 3.0)
• Moving Average Source (default: WMA)

See signal primitives, usage in published strategies and more on WOBR StrategyVerse.