Wavelet-ACF Inertia Breakout System
Family: breakout · Regime: trending · Complexity: high · Asset classes: FX, Equity Indices, Commodities · Timeframes: H1, H4
Thesis
Market breakouts of daily structural levels (H/L) are significantly more likely to persist if the price series exhibits positive autocorrelation (ACF) and the breakout energy is confirmed in the low-frequency detail coefficients of a Wavelet Transform, provided that order-flow sentiment (CVD) confirms liquidity participation.
Components
- Autocorrelation Function (ACF) (regime) — Identifies the regime; values > 0 indicate trend persistence (positive serial correlation), ensuring the breakout has statistical inertia.
- FakeCandle (direction) — Provides the directional bias based on modified market structure visualization; acts as the primary trend filter.
- Daily High Low MTF (entry) — The entry trigger; breaks of the previous day's absolute high/low signify a shift in daily market structure.
- Gator Oscillator (exit) — Used to detect momentum exhaustion (the 'sated' phase) where the histograms shrink, signaling an exit before reversal.
- GHOST OrderFlow Dashboard — DerivEAPro v10 (risk) — Determines position sizing and stop loss placement based on momentum angle (CompassMapping) and CVD sentiment.
- Discrete Wavelet Transform (DWT) (volatility_filter) — Filters out high-frequency market noise; entry is only permitted when the detail coefficient (cycle energy) aligns with the breakout direction.
Known failure conditions
- ACF remains near zero for extended periods, indicating a random walk where breakouts lack follow-through.
- GHOST Dashboard fails to provide data due to JSON integration errors, disabling risk calculations.
- Market enters a 'choppy' regime where DWT detail coefficients flip rapidly without price progression.
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