Polynomial Darvas Zone Breakout

Family: trend_following · Regime: trending · Complexity: high · Asset classes: FX, Equities, Crypto · Timeframes: M15, H1

Thesis

Market trends are best exploited by entering at 'points of least resistance' (Low Volume Nodes) once a structural breakout (Darvas) is confirmed by a high-fidelity polynomial trend filter (SGF) and higher-timeframe consensus (Heatmap). MdAE provides a volatility-adjusted cushion that accounts for the model's prediction error.

Components

• Darvas Boxes Modern/Classic (regime) — Filters for established structural trends; long only above the top of the box, short only below the bottom.
• Savitzky-Golay Filter (SGF) (direction) — Determines the immediate intraday trend direction using polynomial regression to minimize the noise found in standard SMAs.
• Dynamic Supply and Demand Zones [AlgoAlpha] (entry) — Identifies low volume nodes (LVNs) to time entries at structural inefficiencies rather than chasing momentum.
• HiLo Activator 02 (exit) — Acts as a trailing stop-loss mechanism that reacts to the shift in High/Low averages to capture trend exhaustion.
• Median Absolute Error (risk) — Provides a robust, outlier-resistant volatility measure to set initial stop-loss distances and scale position sizes.
• Heatmap Framework (confirmation) — Ensures multi-timeframe alignment, preventing entries against the dominant higher-horizon trend.

Known failure conditions

• Price spends more than 50% of the session within the Darvas Box range without a breakout.
• The Savitzky-Golay Filter shows frequent slope inversions (oscillations) within a 10-bar window.
• MdAE spikes to >3x the 100-bar average, indicating extreme volatility where the polynomial filter loses predictive value.

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