Cleaning Financial Data Using SSA and MSSA

Abstract

We introduce a powerful method for cleaning time series - Multi-Channel Singular Spectrum Analysis (MSSA). “Cleaning” means filling data gaps and removing unphysical spikes, which are chronic problems. MSSA utilizes all available information in “time” and “space” with autocorrelations, correlations, and lagged correlations. MSSA performs demonstrably better than other methods. Here we present tests using MSSA to fill data gaps, with positive results. Spike removal is in a separate paper.

Keywords: cleaning time series, Multi-Channel Singular Spectrum Analysis, MSSA, filling data gaps, removing unphysical spikes, correlations, lagged correlations, autocorrelations

JEL Classification: C1, C14, C22, C63, E44, F65, G1, Y1