KNN-Volume VWAP Pullback Scalper

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Equities, Forex (Major Pairs) · Timeframes: M15, H1

Thesis

Market trends are driven by institutional volume (VWAP), but retail sentiment (Stochastics) creates 'noise' pullbacks. By using KNN to classify the true volume-weighted regime, we can exploit these pullbacks as high-probability re-entry points when a Fisher-transformed momentum cycle (Solar Wind) confirms the resumption of the trend.

Components

• Volume SuperTrend AI (Expo) (regime) — Identifies the dominant regime using KNN-classified VWMA trends to ensure entry is with the smart money flow.
• VWAP + EMA Cross Pullback (direction) — Detects specific institutional mean-reversion pullbacks within the established KNN regime.
• Stochastic Oscillator (entry) — Provides a tactical entry trigger when price momentum recovers from an oversold/overbought state during the pullback.
• Bollinger Bands (Standard) (exit) — Acts as a volatility-based dynamic target, targeting the opposite band to capture the full mean-reversion swing.
• Root Mean Squared Error (RMSE) (risk) — Determines position size and stop-loss distance based on recent prediction error (volatility) relative to the EMA.
• Solar Wind NRP (MQL5) (confirmation) — Filters out false breakouts by ensuring the Fisher Transform cycle has officially turned in the direction of the trade.

Known failure conditions

• KNN regime classification alternates signals every 3-5 bars (regime noise).
• RMSE volatility spikes consistently hit stop losses before Solar Wind confirms a cycle completion.
• Price consistently 'rides the bands' in a trend, making Bollinger Band exits premature or impossible.

Explore the full interactive blueprint with parameter ranges and evidence on WOBR StrategyVerse, or generate this strategy as an MT4/MT5 Expert Advisor with QuantMogul AI Engine (free download).