Neural-ICT Volatility Expansion Strategy

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Forex, US Equities (Indices), Commodities (Gold) · Timeframes: 15m, 1h

Thesis

Market inefficiencies (FVGs) represent institutional liquidity gaps that act as magnets during momentum expansions. By combining these gaps with a non-linear confirmation tool (Neural Network) and a regime filter (SuperTrend), we can isolate high-probability trend continuation plays that occur only when volatility is sufficient to carry the trade to its target. The NNind's use of CLV (Close Location Value) provides a distinct edge over standard RSI by identifying the strength of the 'close' within the candle range, filtering out weak breakouts.

Components

Known failure conditions

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