Post-Shock Reversal
Measures the reversal tendency after a shock event. Combines mean reversion distance, run exhaustion, and volatility normalization.
Why AlgoZilla Uses Post-Shock Reversal
Post-shock periods often offer the highest alpha opportunities. The model learns optimal re-entry timing after different shock types per coin.
Feature Variants
AlgoZilla expands every base indicator into multiple variants: raw values, delta (rate of change over 8/12/24 bars), divergences, and multi-timeframe computations across 2H, 4H, 8H, 12H, and 24H horizons. This is what sets AlgoZilla apart: 170+ features, each retrained every two weeks per coin.
Variants: 4 variants
Part of a Bigger Picture
No single indicator drives AlgoZilla decisions. This is one of 170+ features feeding into a machine learning ensemble, retrained every two weeks per coin. The model learns which features matter in each market regime.
