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Flexible multivariate GARCH modeling with an application to international stock markets

Mostra el registre parcial de l'element Ledoit, Olivier Santa Clara, Pedro Wolf, Michael
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa 2017-07-26T10:48:13Z 2017-07-26T10:48:13Z 2001-10-01
dc.identifier.citation Review of Economics and Statistics 85, 735-747, 2003
dc.description.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.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 578
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.title Flexible multivariate GARCH modeling with an application to international stock markets
dc.type info:eu-repo/semantics/workingPaper 2017-07-23T02:06:27Z
dc.subject.keyword diagonal-vech model multivariate garch
dc.subject.keyword unrestricted estimation
dc.subject.keyword Finance and Accounting
dc.rights.accessRights info:eu-repo/semantics/openAccess

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