Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

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• dc.contributor.author Ledoit, Olivierca
• dc.contributor.author Wolf, Michaelca
• dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
• dc.date.accessioned 2017-07-26T10:50:29Z
• dc.date.available 2017-07-26T10:50:29Z
• dc.date.issued 2001-11-01
• dc.date.modified 2017-07-23T02:06:33Z
• dc.description.abstract This paper proposes to estimate the covariance matrix of stock returns by an optimally weighted average of two existing estimators: the sample covariance matrix and single-index covariance matrix. This method is generally known as shrinkage, and it is standard in decision theory and in empirical Bayesian statistics. Our shrinkage estimator can be seen as a way to account for extra-market covariance without having to specify an arbitrary multi-factor structure. For NYSE and AMEX stock returns from 1972 to 1995, it can be used to select portfolios with significantly lower out-of-sample variance than a set of existing estimators, including multi-factor models.
• dc.format.mimetype application/pdfca
• dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=586
• dc.identifier.citation Journal of Empirical Finance 10, 603-621, 2003
• dc.identifier.uri http://hdl.handle.net/10230/656
• dc.language.iso eng
• dc.relation.ispartofseries Economics and Business Working Papers Series; 586
• 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.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
• dc.subject.keyword covariance matrix estimation
• dc.subject.keyword factor models
• dc.subject.keyword portofolio selection
• dc.subject.keyword shrinkage
• dc.subject.keyword Finance and Accounting
• dc.title Improved estimation of the covariance matrix of stock returns with an application to portofolio selectionca
• dc.type info:eu-repo/semantics/workingPaper