CoherIQs

Originally developed for examining scale-dependent correlations between the El Nino-Southern Oscillation and Indian Monsoons, wavelet coherence is a powerful method for analyzing lead-lag relationships embedding in time series data using wavelet transforms. While becoming more popular in academic settings to publish research, current coherence implementations are limited to dependencies within in R, MATLAB, or Python environments. These packages rely on outdated and inefficient transforms on the backend, limiting their use to analysis of small batches of historical data.

The CoherIQs project is focused on broadening the scope of use for wavelet coherence by optimizing the underlying algorithms and providing a user-friendly interface for industry professionals. Currently, the opus is centered around a live dashboard for quantitative analysis that displays the lead-lag cycles as they appear from incoming data.

Background on wavelet coherence analysis and its applications in finance and economics can be found in the Literature section.