Squeeze Momentum
Measures momentum during Bollinger Band squeezes — periods of low volatility that often precede explosive moves. Combines Keltner Channels with Bollinger Bands.
Why AlgoZilla Uses Squeeze Momentum
Squeeze events are high-conviction setups. The model learns that momentum direction during a squeeze is a strong predictor of the breakout direction.
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.
Variants: 4 variants including squeeze state, momentum direction, and duration
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.
