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Flexible Multivariate GARCH Modeling with an Application to International Stock Markets

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Author Info
Olivier Ledoit (Credit Suisse First Boston)
Pedro Santa-Clara (The Anderson School, UCLA)
Michael Wolf (Universitat Pompeu Fabra)
Abstract

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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File URL: http://www.mitpressjournals.org/doi/pdfplus/10.1162/003465303322369858
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Publisher Info
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:735-747

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