GARCH-Adaptive Momentum Accelerator

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

Thesis

Trends persist due to behavioral herding, but timing entries at the local 'acceleration' point of momentum (TSI_CD) while scaling risk based on volatility clustering (GARCH) provides an edge by maximizing exposure during stable trends and minimizing it during high-uncertainty shocks.

Components

• Simple Moving Average (SMA) (regime) — Identifies the institutional-grade long-term trend bias to ensure trades align with major flow.
• Momentum Oscillator (direction) — Acts as a medium-term directional filter to ensure the trend has sufficient velocity.
• TSI Convergence Divergence (TSI_CD) (entry) — Captures the second-derivative momentum shift (acceleration/deceleration) for precise entry timing.
• Chandelier Exit (Heiken Ashi) (exit) — Provides a volatility-adjusted trailing stop that accounts for Heiken Ashi smoothing to reduce whipsaws.
• Conditional Volatility (CV) (risk) — Uses GARCH(1,1) logic to scale position size based on current volatility clustering, reducing exposure during high-risk regimes.
• RSIOMA (RSI of Moving Average) (confirmation) — Smoothed RSI of an EMA filters out market noise, confirming that the momentum is structural rather than erratic.

Known failure conditions

• SMA slope remains flat for extended periods while Momentum oscillates wildly (regime breakdown).
• Realized volatility significantly exceeds the GARCH(1,1) predicted conditional volatility during news events.
• TSI_CD produces alternating signals (Green/Red) on consecutive bars during low-liquidity sessions.

Explore the full interactive blueprint with parameter ranges and evidence on WOBR StrategyVerse, or generate this strategy as an MT4/MT5 Expert Advisor with QuantMogul AI Engine (free download).