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Flexible Multivariate GARCH Modeling with an Application to International Stock Markets Author info | Abstract | Publisher info | Download info | Related research | Statistics Olivier Ledoit (Credit Suisse First Boston)
Pedro Santa-Clara (The Anderson School, UCLA)
Michael Wolf (Universitat Pompeu Fabra)
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. Copyright (c) 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Article provided by MIT Press in its journal Review of Economics and Statistics .
Volume (Year): 85 (2003)
Issue (Month): 3 (07)
Pages: 735-747
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Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:735-747Contact details of provider: Web page: http://mitpress.mit.edu/journals/
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