LSTM-Fractal Structural Momentum Trader
Family: hybrid · Regime: trending · Complexity: high · Asset classes: Forex, Equity Indices, Commodities · Timeframes: M15, H1
Thesis
Market structure shifts (CISD) following liquidity sweeps are more reliable when they align with an AI-optimized volatility regime. The hypothesis is that the LSTM can successfully identify 'Trend Quality' better than static ATR, and the Fractal Model captures the exact moment of institutional re-entry, while CCI filters for the momentum recovery required to confirm the move.
Components
- ML SuperTrend (Ultimate) - Auto-Optimized AI with LSTM (regime) — Defines the underlying regime by using LSTM to adapt ATR multipliers to current volatility clusters, filtering out noise in choppy regimes.
- Open Source Fractal Model (direction) — Identifies internal market structure shifts (MSS) and 'Change in Sub-structure' (CISD) to provide directional bias based on institutional candle sweeps.
- Commodity Channel Index (CCI) (entry) — Used as a momentum-based trigger to enter the trade once price recovers from a mean-reversion extreme within the trend.
- Pivot Point S&R with GMT Correction (exit) — Provides objective, time-aligned horizontal levels for profit taking based on floor-pivot math.
- iExposure (risk) — Monitors net lot exposure and aggregate symbol-level risk to prevent over-leveraging across multiple fractal setups.
- Bears Power (confirmation) — Confirms that bearish pressure is receding (for longs) or dominant (for shorts) relative to the EMA baseline.
Known failure conditions
- ML SuperTrend 'Factor' oscillates rapidly in low-volatility environments, causing regime flip-flopping.
- Fractal CISD levels are consistently breached without follow-through, indicating a failure of the liquidity-sweep hypothesis.
- Daily Pivot levels (R1/S1) are narrower than the average hourly candle, suggesting extreme compression.
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