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Flexible multivariate GARCH modeling with an application to international stock markets
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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 nev^ estimator with a number of existing ones.
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Review of Economics and Statistics, V.85(3), p. 735-747