Tests for Breaks in the Conditional Co-movements of Asset Returns

We propose procedures designed to uncover structural breaks in the co-movements of financial markets. A reduced form approach is introduced that can be considered as a two-stage method for reducing the dimensionality of multivariate heteroskedastic conditional volatility models through marginalization. The main advantage is that one can use returns normalized by volatility filters that are purely data-driven and construct general conditional covariance dynamic specifications. The main thrust of our procedure is to examine change-points in the co-movements of normalized returns. The tests allow for strong and weak dependent as well as leptokurtic processes. We document, using a ten year period of two representative high frequency FX series, that regression models with non-Gaussian errors describe adequately their co-movements. Change-points are detected in the conditional covariance of the DM/US$ and YN/US$ normalized returns over the decade 1986-1996. Nous proposons des procédures pour tester le changement structurel dans les co-mouvements conditionnels d'actifs financiers. L'approche est basée sur la forme réduite et la procédure à deux étapes. L'avantage est qu'on utilise des rendements normalisés par leurs volatilités, une transformation qui peut s'effectuer sans intervention explicite d'un modèle paramétrique. La deuxième étape consiste à tester le changement structurel dans les corrélations conditionnelles. Le papier contient une application empirique avec des taux de changes.