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.
Year of publication: |
2003
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Authors: | Ledoit, Olivier ; Santa-Clara, Pedro ; Wolf, Michael |
Published in: |
The Review of Economics and Statistics. - MIT Press. - Vol. 85.2003, 3, p. 735-747
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Publisher: |
MIT Press |
Saved in:
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