A Flexible Dynamic Correlation Model

Abstract

Existing multivariate GARCH models either impose strong restrictions on the parameters or do not guarantee a well-defined (positive definite) covariance matrix. I discuss all main Multivariate GARCH models and focus on the BEKK model for which it is shown that the covariance and correlation is not adequately specified under certain conditions. This implies that any analysis of the persistence and the asymmetry of the correlation is difficult and potentially inaccurate. I therefore propose a new Flexible Dynamic Correlation (FDC) model that parameterizes the conditional correlation directly and eliminates various shortcomings of the existing Multivariate GARCH models. Empirical results of daily and monthly returns of four international stock market indices reveal that correlations exhibit different degrees of persistence and different asymmetric reactions to shocks than variances. In addition, I find that correlations do not always increase with jointly negative shocks implying a justification for international portfolio diversification. Time-varying Correlations

Keywords: Multivariate GARCH, BEKK, Covariance Models,

JEL Classification: C32, C52