FFT Frequency Analysis and Band-Pass Filtering for Market Series

Summary

This indicator applies a Fast Fourier Transform to a selected market series over a configurable lookback window. It decomposes the data into frequency components, displays a power spectrum, and can list prominent components with their estimated cycle periods and relative power. Users can optionally standardize the input, inspect a reconstructed series, or retain only a selected range of frequency components before applying an inverse transform. A moving-window option repeats the filtering process for each bar and plots the latest filtered value.

The tool is presented as a way to inspect cyclical structure and remove selected frequency content, including high-frequency variation. The description explains its outputs and controls but does not provide trading rules, empirical results, or evidence that detected cycles persist. FFT filtering depends on the chosen window, frequency range, and data treatment; standardization also changes the scale and does not preserve the series average. The filtered output should therefore be treated as an analytical transformation, not a demonstrated forecast or standalone trading signal.

Key ideas

• The FFT decomposes a selected series into frequency components whose squared magnitudes represent spectral power.
• A power spectrum and table help inspect component strength and estimated cycle periods.
• An inverse transform reconstructs the series after retaining a user-selected frequency band.
• A moving-window option applies the filter repeatedly and exposes a filtered value for each bar.
• The document provides no evidence that filtered cycles predict future market behavior.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.