Wavelet-Filtered Structural Breakout

Family: trend_following · Regime: trending · Complexity: high · Asset classes: FX, Equities, Crypto · Timeframes: H1, H4

Thesis

The hypothesis is that price expansion beyond daily structural levels (DHL) is more likely to sustain a trend if the cyclical high-frequency noise (DWT detail) is aligned with medium-term volatility trends (UTBot) and confirmed by momentum spread (Braid Filter). The DWT acts as a noise-reduction filter to ensure the breakout is not a temporary mean-reversion spike.

Components

• Discrete Wavelet Transform (DWT) (regime) — Acts as a regime filter by identifying the 'detail' (noise/cycle) phase. A positive detail coefficient suggests a high-frequency cyclical upswing within the larger trend.
• UTBot Alerts (direction) — Provides medium-term trend direction. The ATR-based trailing stop ensures we are on the right side of volatility-adjusted momentum.
• Daily High Low (entry) — Market structure entry trigger. A breakout of the previous day's high/low validates that current price action has escaped the previous session's equilibrium.
• SuperTrend (exit) — Used for exit. Its binary trend state (1 or -1) provides a trailing mechanism that accounts for volatility contraction and expansion.
• GAS Price Levels (risk) — Provides structural risk levels. The Bollinger Band component within GAS serves as a dynamic floor/ceiling for stop-loss placement, while ATR defines position size.
• Braid Filter (ATR Optimized) (volatility_filter) — Ensures entry only occurs during periods of expanding spread between short and long-term moving averages, filtering out low-momentum noise.

Known failure conditions

• The strategy enters a 'choppy' regime where ATR-based stops are repeatedly hit before a Daily High/Low breakout can develop trend extension.
• The DWT detail coefficients oscillate rapidly around zero, creating signal lag that leads to late entries.
• Market regime shifts to permanent low-volatility where the Braid Filter spread never exceeds the ATR threshold.

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