Magnitude Delta Structural Trend Follower

Family: trend_following · Regime: trending · Complexity: high · Asset classes: Forex, Equities, Indices · Timeframes: H1, H4, D1

Thesis

Market trends are confirmed when the maximum 'effort' (candle body size) of one side significantly outweighs the other. By combining this volatility-intensity (SHL2) with smoothed price-range momentum (AF) and structural volume filters (POC), we can identify high-conviction entries via candlestick patterns that signal the resumption of the primary trend after minor pullbacks. The edge lies in the confluence of magnitude, direction, and volume-based support/resistance.

Components

• Size Highs and Lows 2 (regime) — Determines the 'magnitude regime' by comparing the single largest bullish candle vs the largest bearish candle in the lookback window; this filters for aggressive directional volatility.
• Average Force (direction) — Provides a smoothed momentum baseline to ensure the entry is aligned with the intermediate price trend relative to its recent range.
• Pattern Recognition Master (entry) — Acts as the precise trigger mechanism, identifying structural exhaustion or reversal patterns (like Engulfing or Hammers) within the identified regime.
• Chandelier Exit (exit) — A trailing volatility stop that allows the trend to breathe while protecting gains against sharp reversals.
• Volume Profile + Pivot Levels [ChartPrime] (risk) — Uses structural Pivot Levels for stop placement and the Point of Control (POC) as a secondary filter to avoid 'value' areas where price tends to stall.

Known failure conditions

• Persistence of low-volatility 'doji' regimes where SHL2 delta remains near zero.
• Price oscillating around the Volume Profile POC, leading to frequent Chandelier Exit triggers.
• Asset-specific pip thresholds in the Pattern Recognition indicator failing to trigger on high-value indices.

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