Adaptive Drift Breakout System (ADBS)

Family: trend_following · Regime: trending · Complexity: high · Asset classes: Equities, Major FX Pairs (using Tick Volume), Commodities · Timeframes: 1H, 4H, D1

Thesis

Market trends are most reliable when characterized by 'statistical drift' (non-random motion) and confirmed by cumulative volume flow. By using an adaptive envelope to filter noise and entering only on Keltner volatility breakouts, we capture the transition from balance to imbalance. The exit logic acknowledges that trends often terminate at previous areas of institutional supply/demand, while the PSAR provides a dynamic fail-safe for unexpected reversals.

Components

• Jurik Adaptive Envelope Bands (regime) — Establishes a volatility-adjusted baseline that adapts to noise levels, ensuring the trend hasn't already overextended.
• McGinley Dynamic (direction) — Acts as the 'smarter' trend filter that stays closer to price than an EMA, reducing lag in trend identification.
• Keltner Channels (entry) — The specific entry trigger; a breakout beyond the KC upper/lower band signals a volatility-backed momentum surge.
• Supply & Demand Zones (NNFX) (exit) — Identifies institutional 'walls' where price is likely to exhaust, providing structural profit targets.
• Parabolic SAR (risk) — Provides a non-subjective trailing stop that accelerates as the trend matures.
• Price and Volume Trend (PVT) (confirmation) — Confirms that price movement is supported by cumulative volume flow, preventing 'hollow' breakouts.
• Asset Drift Model (ADM) (volatility_filter) — Filters for regimes with statistically significant non-random drift to avoid whipsaws in mean-reverting environments.

Known failure conditions

• Prolonged periods where Variance Ratio (VR) stays near 1.0 (pure random walk).
• Asset exhibits frequent 'fakeouts' where KC breaks immediately revert to the McGinley Dynamic.
• Tick volume data is unavailable or highly manipulated (e.g., low-tier offshore brokers).

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