Wavelet analysis of financial contagion

Abstract

In this paper we estimate a simultaneous equation model fitted to financial returns in order to disentangle the role played by common shock and idiosyncratic shocks in shaping the co-movement between asset returns during periods of calm and financial turbulence. For this purpose we use wavelet analysis, and, in particular, the Maximum Overlapping Discrete Wavelet Transform, to decompose the covariance matrix of the asset returns on a scale by scale basis, where each scale is associated to a given frequency range. This decomposition will give enough moment conditions to identify the role played by common and idiosyncratic shocks. A Montecarlo simulation experiment shows that our testing methodology has good size and power properties to test for the null of no contagion. Finally, using Full Information Maximum Likelihood, we fit our model to test for the presence of contagion within the East Asian region stock markets during the 1997-1998 period of financial turbulence.