Statistical Drift & Structural Pivot Hybrid

Family: trend_following · Regime: trending · Complexity: medium · Asset classes: Equities, FX Major Pairs, Commodities · Timeframes: H1, H4, D1

Thesis

Market drift is not a random walk during periods of high economic significance; assets exhibiting statistically significant drift (HAC-validated) tend to persist in that direction. By entering at structural price-action pivots (Roshaneforde) within these drift regimes and using volatility-based trailing stops, we can capture the meat of the trend while filtering out 'fake-outs' occurring in non-trending variance regimes.

Components

• Asset Drift Model (ADM) (regime) — Provides the statistical filter to ensure the asset is exhibiting significant non-random drift before attempting to trend-follow.
• Heiken Ashi (direction) — Filters out minor price noise and ensures that the immediate momentum (direction) is synchronized with the long-term drift.
• Roshaneforde Pivot Levels (entry) — Identifies structural support/resistance zones based on reversal patterns for precise entry execution.
• ATR SL Finder (exit) — Provides a volatility-adjusted trailing exit that adapts to market expansion and contraction.
• Darvas Boxes Modern/Classic (risk) — Defines the technical 'floor' or 'ceiling' for stop placement and position sizing based on confirmed consolidation levels.

Known failure conditions

• Price stays within the Darvas Box for > 3 * HORIZON periods (drift exhaustion).
• Variance Ratio (VR) falls below 1.0, indicating a transition to mean-reversion.
• Asset Drift Model t-stat falls within (-1.96, 1.96), showing a lack of statistical significance.

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