Flexible Multivariate GARCH Modeling with an Application to International Stock Markets
This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the new estimator with a number of existing ones. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Volume (Year): 85 (2003)
Issue (Month): 3 (August)
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