Cointegrated Persistence Trend Long
Family: trend_following · Regime: trending · Complexity: high · Asset classes: Equities, ETFs · Timeframes: H1, D1
Thesis
Assets that are cointegrated with a benchmark but exhibit positive autocorrelation (trend persistence) are less likely to experience random idiosyncratic failures. Entering these assets when momentum recovers from an oversold state (Williams %R) within a larger trend (Sherif Hilo) captures the 'beta' of the market with the 'alpha' of momentum persistence.
Components
- Commodity Channel Index (CCI) (regime) — Ensures the asset is in a positive momentum state relative to its mean deviation before entry.
- Sherif Hilo (direction) — Establishes the primary trend bias using price extremes to filter out minor fluctuations.
- Williams %R (entry) — Provides the tactical entry trigger by identifying the end of an oversold pullback within the uptrend.
- Bollinger Bands (Standard) (exit) — Used for profit-taking when price reaches an expansion extreme (Upper Band).
- Bullish Pivot Detector (risk) — Identifies structural support levels to define the hard stop-loss and validates local demand.
- Cointegration (COINTEGRATION) (confirmation) — Validates that the asset is behaving predictably relative to a benchmark, reducing the risk of idiosyncratic 'black swan' price action.
- Autocorrelation Function (ACF) (volatility_filter) — Filters for 'trend persistence' (positive autocorrelation) to ensure the move is not a mean-reverting noise spike.
Known failure conditions
- Cointegration ADF statistic remains above -2.0 for extended periods, indicating a breakdown in the relationship with the benchmark.
- ACF stays negative (mean-reverting) during a price breakout, suggesting the breakout is exhaustive rather than persistent.
- Multiple Bullish Pivot 'Running Lows' are breached in rapid succession.
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