Fisher-Neural MAPE Stability Trend

Family: hybrid · Regime: trending · Complexity: medium · Asset classes: Forex, Indices · Timeframes: H1

Thesis

Market momentum signals (Fisher Transform) are most reliable when the underlying price action exhibits low error (MAPE) relative to a predictive model, suggesting a 'clean' trend that is likely to be confirmed by pre-trained neural patterns. By anchoring risk to session-based volatility levels (ATR Fib), the strategy captures high-probability expansions with structured exit targets.

Components

• Indicator Sample (Template) (regime) — Acts as a 'warm-up' filter to ensure the trading environment has sufficient historical data (iBars) before execution.
• Unsupported matrix.sort method in UDF (Diagnostic) (direction) — Provides a raw price-action trend filter; despite the matrix wrapper, it effectively isolates current price vs. historical price for direction.
• Fisher Transform (EarnForex) (entry) — Normalizes price extremes to identify turning points via zero-line crossovers.
• Average True Range (NNFX Version) (exit) — Used for a dynamic trailing stop or profit target calculation to account for local volatility expansion.
• ATR Fib (risk) — Provides session-based structural anchors for stop loss placement and position sizing calculation.
• Neural Network Indicator (NNind) (confirmation) — Filters momentum signals through a pre-trained MLP to ensure the entry coincides with learned price patterns.
• Mean Absolute Percentage Error (MAPE) (volatility_filter) — Filters out periods of high 'unpredictability' where price deviates too wildly from its internal model (EMA), avoiding erratic markets.

Known failure conditions

• MAPE remains above 1.5% for extended periods, indicating the asset is too volatile for the model's smoothing.
• Price consistently oscillates around the Fisher 0-line without ATR expansion.
• Neural Network output clusters at 50 (neutral), providing no directional confirmation.

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