GARCH-RWI Multi-Confluence Trend Engine

Family: trend_following · Regime: trending · Complexity: high · Asset classes: Equities, FX, Crypto · Timeframes: H1, H4, D1

Thesis

The hypothesis is that financial markets exhibit periods of non-random, persistent flow (trends) that can be statistically separated from noise using the Random Walk Index. By combining this regime filter with GARCH-based risk clustering and a multi-factor confluence score (IAE), we can identify entries where momentum is backed by structural trend strength. The edge lies in the dynamic adjustment of risk relative to conditional volatility, allowing the strategy to survive noise while capturing high-order trends.

Components

Known failure conditions

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