Variance Ratio
Tests whether returns follow a random walk by comparing variance at different horizons. Deviation from 1.0 indicates predictability.
Why AlgoZilla Uses Variance Ratio
When variance ratio deviates significantly from 1.0, the market has exploitable structure. The model increases conviction on signals in these periods.
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: 1 variant (raw value)
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.
