KNN-Volume Institutional Flow Composite

Family: hybrid · Regime: trending · Complexity: high · Asset classes: FX, Equities, Crypto · Timeframes: 15m, 1h, 4h

Thesis

Institutional momentum (Order Blocks) is most likely to persist when the local price neighborhood (KNN) and cyclic phase (CG) align with established volume clusters (POC). The inclusion of a look-ahead regime filter serves to establish a 'maximum potential' baseline for the logic before removing the leak for live deployment.

Components

• Unsupported named const comparison ternary negative history (regime) — Acts as a theoretical 'Perfect Information' filter by referencing the next bar's close, used here to validate if the underlying signals align with actual future direction during backtesting.
• AI Trend Navigator [K-Neighbor] (direction) — Identifies the local momentum 'neighborhood' to ensure trades are taken in the direction of the dominant non-linear trend.
• Sonarlab - Order Blocks (entry) — Identifies high-momentum institutional footprints (Order Blocks) to provide specific price levels for entry.
• MACD (exit) — Provides a momentum-based exit signal to capture the meat of the move before exhaustion.
• Volume Profile + Pivot Levels [ChartPrime] (risk) — Utilizes the Point of Control (POC) as a dynamic support/resistance level for stop-loss placement.
• Ehlers Center of Gravity (CG) (confirmation) — Confirm cycle turning points with zero lag to filter out late entries in maturing trends.

Known failure conditions

• The Volume Profile POC shifts significantly immediately after entry, indicating a 'HVG' (High Volume Gap).
• Ehlers CG oscillates around its balance point for >5 bars (market stagnation).
• Strategy fails to maintain a Win Rate > 40% even with the theoretical look-ahead regime filter.

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).