Adaptive Motive Structure Trader
Family: trend_following · Regime: trending · Complexity: high · Asset classes: FX, Equities, Crypto · Timeframes: M15, H1
Thesis
The hypothesis is that markets move in fractal motive waves, and the highest probability entries occur when a 'Change of Character' (CHoCH) confirms the end of a corrective wave (2 or 4) while aligning with adaptive momentum (KAMA). By requiring higher-timeframe alignment via the Dashboard and using volatility-adjusted trailing stops (SuperTrend), we capture the most efficient portion of Wave 3 and 5 impulses while filtering out low-efficiency ranging periods.
Components
- MultiKAMA (TyphooN) (regime) — Provides a volatility-adjusted trend filter. We only trade when price is on the correct side of the adaptive mean and the Efficiency Ratio (ER) suggests a trending environment.
- ProfitRobots Dashboard Template (direction) — Ensures higher timeframe (HTF) alignment. The hypothesis requires the H4 trend (defined by Price > H4 KAMA) to match the M15/H1 entry timeframe.
- BOS_CHoCH_Detector (entry) — Acts as the precise entry trigger by identifying the transition from corrective phases (CHoCH) to impulsive trend continuations (BOS).
- SuperTrend (exit) — Provides a dynamic trailing stop that accounts for ATR-based volatility, allowing the trade to breathe during motive waves but exiting on clear trend reversals.
- Elliott Wave [LuxAlgo] (risk) — Used to identify the 'location' within the market cycle. Entries are prioritized during projected Wave 3 or Wave 5 impulses, with stop-losses placed at the Wave 2 or 4 pivots.
Known failure conditions
- Price enters a protracted sideways range where the Efficiency Ratio (ER) remains below 0.3 for extended periods.
- Elliott Wave pivots are frequently invalidated (e.g., Wave 4 overlapping Wave 1), indicating a lack of clear impulsive structure.
- High frequency of CHoCH signals without follow-through BOS, indicating market exhaustion.
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