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

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  • Elena Andreou
  • Eric Ghysels

Abstract

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 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. 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.
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  • Elena Andreou & Eric Ghysels, 2002. "Tests for Breaks in the Conditional Co-movements of Asset Returns," CIRANO Working Papers 2002s-59, CIRANO.
  • Handle: RePEc:cir:cirwor:2002s-59
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    3. Marco Barassi & Lajos Horváth & Yuqian Zhao, 2020. "Change‐Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 340-349, April.
    4. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.

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    More about this item

    Keywords

    Change-point tests; multivariate GARCH models; conditional covariance; high-frequency financial data; Changement structurel; ARCH; corrélations conditionnelles; données de haute fréquence;
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