Measuring Spot Variance Spillovers When (Co)Variances are Time-Varying - The Case of Multivariate GARCH Models

Abstract

We propose global and disaggregated spillover indices that allow us to assess variance and covariance spillovers, locally in time and conditionally on time-t information. Key to our approach is the vector moving average representation of the half-vectorized 'squared' multivariate GARCH process of the popular BEKK model. In an empirical application to a four-dimensional system of broad asset classes (equity, fixed income, foreign exchange and commodities), we illustrate the new spillover indices at various levels of (dis)aggregation. Moreover, we demonstrate that they are informative of the value-at-risk violations of portfolios composed of the considered asset classes.