Flexible multivariate GARCH modeling with an application to international stock markets

Olivier Ledoit, Pedro Santa-Clara and Michael Wolf

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: The goal of this paper is to estimate time-varying covariance matrices. Since the covariance matrix of financial returns is known to change through time and is an essential ingredient in risk measurement, portfolio selection, and tests of asset pricing models, this is a very important problem in practice. Our model of choice is the Diagonal-Vech version of the Multivariate GARCH(1,1) model. The problem is that the estimation of the general Diagonal-Vech model model is numerically infeasible in dimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contribution is to propose an alternative estimation method that is numerically feasible, produces positive semi-definite 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 to a number of existing ones.

Keywords: Diagonal-Vech model multivariate GARCH; unrestricted estimation (search for similar items in EconPapers)
JEL-codes: C13 C51 C61 G11 G15 (search for similar items in EconPapers)
Date: 2001-10
New Economics Papers: this item is included in nep-ecm, nep-ent, nep-ets, nep-fmk and nep-net
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Flexible Multivariate GARCH Modeling with an Application to International Stock Markets (2003)
Working Paper: Flexible Multivariate GARCH Modeling With an Application to International Stock Markets (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:578

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