Volumatic MAPE Mean Reversion

Family: mean_reversion · Regime: high_vol · Complexity: high · Asset classes: FX, Equities, Crypto · Timeframes: 15M, 1H

Thesis

Market participants often overreact to price movements, pushing prices to high-volume extremes (absorption points). By measuring the statistical error (MAPE) between price and its mean, we can identify overextended states and trade reversals at these high-volume structural levels (BigBeluga). Risk is managed through objective daily boundaries (MTF) rather than arbitrary pip values.

Components

• Supported for-in empty array slice result negative body history (regime) — Acts as a 'Runtime Integrity' filter; ensures the execution environment is handling array slicing correctly before signals are processed.
• Unsupported table.new modes Test Indicator (direction) — Provides the raw price series (close) for directional bias, ensuring no smoothing lag in trend detection.
• Volumatic Support/Resistance Levels [BigBeluga] (entry) — Identifies price levels where high-volume absorption occurs, suggesting a structural turning point.
• Ichimoku Kinko Hyo (exit) — The Kijun-sen (Base Line) provides a medium-term equilibrium level for trend-following exits.
• Daily High Low MTF (risk) — Utilizes fixed higher-timeframe boundaries for stop-loss placement and volatility-adjusted position sizing.
• Mean Absolute Percentage Error (MAPE) (volatility_filter) — Filters for high-deviation environments; only trades when price error (deviation from mean) is sufficient to expect a high-momentum reversal.

Known failure conditions

• MAPE consistently below 0.1% indicating a 'dead' market.
• Price creates 'gap-and-go' moves that never touch support/resistance bands.
• HTF Daily High/Low range is tighter than 2x ATR(14), making R:R impossible.

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