Dominant Cycle Analysis
Spectral analysis of price data to identify the dominant cycle length. Uses FFT and autocorrelation to find recurring periodic patterns.
Why AlgoZilla Uses Dominant Cycle Analysis
Knowing the dominant cycle helps the model time entries relative to the cycle phase. Most useful for coins with strong cyclical behavior.
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: 3 variants including cycle length, phase, and amplitude
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.
