Spectral Analysis of Asset Prices

Spectral analysis involves decomposing financial time series data into its constituent frequency components to identify cyclical patterns. By using techniques like the Fourier Transform, analysts can identify dominant cycles or periodicities that might not be visible in standard price charts.

In finance, this helps distinguish between random walk behavior and systematic, recurring patterns caused by institutional behavior or scheduled events. This analysis is applied to understand the frequency of market oscillations, which is useful for long-term trend forecasting and timing market entries.

It provides a lens into the structural rhythm of markets, allowing traders to align their strategies with the inherent temporal structure of price action.