Article ID: | iaor201112162 |
Volume: | 65 |
Issue: | 2 |
Start Page Number: | 125 |
End Page Number: | 163 |
Publication Date: | May 2011 |
Journal: | Statistica Neerlandica |
Authors: | McAleer Michael, Caporin Massimiliano |
Keywords: | statistics: multivariate |
Dynamic Asymmetric Multivariate GARCH (DAMGARCH) is a new model that extends the Vector ARMA-GARCH (VARMA-GARCH) model of Ling and McAleer (2003) by introducing multiple thresholds and time-dependent structure in the asymmetry of the conditional variances. Analytical expressions for the news impact surface implied by the new model are also presented. DAMGARCH models the shocks affecting the conditional variances on the basis of an underlying multivariate distribution. It is possible to model explicitly asset-specific shocks and common innovations by partitioning the multivariate density support. This article presents the model structure, describes the implementation issues, and provides the conditions for the existence of a unique stationary solution, and for consistency and asymptotic normality of the quasi-maximum likelihood estimators. The article also presents an empirical example to highlight the usefulness of the new model.