FX Singular Spectrum Analysis

Summary Singular spectrum analysis (SSA) is a method utilized for the analysis of time series arising from dynamical systems. The method is used to capture oscillations from a given time series via the analysis of the eigenspectra of the so-called trajectory matrix. The trajectory matrix is composed of multiple data views. The singular value decomposition (SVD) of the trajectory matrix can be used for rank reduction and noise elimination. We apply SSA in the FX domain and present a comparison with classical FX deconvolution. The algorithm arising from SSA analysis is equivalent to Cadzow FX noise attenuation, a method recently proposed by Trickett (2008). It is important to stress, however, that Cadzow filtering (Cadzow, 1988) is a general framework for noise reduction of signals and images. Cadzow filtering is equivalent to SSA when considering sinusoidal waveforms immersed in additive random noise. The intention of this abstract is to provide a simple explanation of the basic assumptions made in SSA and its application to the modeling of plane waves.