ALMA Fractal-Heikin Momentum Hybrid

Family: trend_following · Regime: trending · Complexity: medium · Asset classes: FX, Equities, Crypto · Timeframes: H1, H4

Thesis

Trend persistence is most predictable when a structural break (Fractals) is confirmed by a low-lag, Gaussian-smoothed trend regime (ALMA) and validated by smoothed momentum (HA Stochastic). By using Heikin-Ashi data for momentum and volatility, we filter out localized price noise, entering only when 'true' trend strength is rising, while exiting at adaptive exhaustion levels.

Components

• ALMA with Floating Levels (regime) — Filters for strong directional momentum (regime) by ensuring price is above/below adaptive Exhaustion levels, preventing entries into overextended trends.
• Trend Break Fractal (direction) — Provides directional bias based on structural market shifts (higher-high/lower-low breaks), ensuring we align with the immediate trend structure.
• OTLIB Stochastic Oscillator (Heikin-Ashi based) (entry) — Uses smoothed momentum to trigger entries on mid-trend pullbacks, reducing noise through HA-based price smoothing.
• RSI Area (Histogram) (exit) — Detects momentum exhaustion at extremes (80/20) to trigger exits before the trend reverses.
• ATR Heiken Ashi (risk) — Dynamically adjusts stop-loss based on smoothed volatility to avoid noise-induced exits.
• Keltner Channels (volatility_filter) — Acts as a 'volatility floor'; entries only occur when price is outside the mid-line to ensure sufficient momentum is present.

Known failure conditions

• Persistent sideways price action leading to OTLIB Stochastic whipsaws.
• ALMA Floating Levels failing to adapt to rapid 'V-shaped' reversals.
• Heikin-Ashi based calculations introducing too much lag for high-frequency volatility shifts.

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