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Editor: Universidad Carlos III de Madrid. Departamento de Estadística

Issued date: 2000-11

Serie-No.: UC3M Working papers. Statistics and Econometrics00-77

Keywords: Covariance matrix estimation , Factor models , Portfolio selection , Shrinkage method

Rights: Atribución-NoComercial-SinDerivadas 3.0 España

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 standardThis 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 multifactor models.+-





Autor: Ledoit, Olivier; Wolf, Michael

Fuente: http://e-archivo.uc3m.es


Introducción



Universidad Carlos III de Madrid Repositorio institucional e-Archivo http:--e-archivo.uc3m.es Departamento de Estadística DES - Working Papers.
Statistics and Econometrics.
WS 2000-11 Improved estimation of the covariance matrix of stock returns with an application to portfolio selection Ledoit, Olivier http:--hdl.handle.net-10016-10089 Descargado de e-Archivo, repositorio institucional de la Universidad Carlos III de Madrid I I I IMPROVED ESTIMATION OF THE COVARIANCE MATRIX OF STOCK RETURNS WITH AN APPLICATION TO PORTFOLIO SELECTION Olivier Ledoit Michael Wolf 00-77 (-) G:::: w 0. « 0. Universidad Carlos III de Madrid Working Paper 00-77 Statistics and Econometrics Series 36 November 2000 Departamento de Estadistica y Econometria Universidad Carlos ID de Madrid Calle Madrid, 126 28903 Getafe (Spain) Fax (34) 91 624-98-49 IMPROVED ESTIMATION OF THE COVARIANCE MATRIX OF STOCK RETURNS WITH AN APPLICATION TO PORTFOLIO SELECTION Olivier Ledoit and Michael Wolf - 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 multifactor models. Keywords: Covariance matrix estimation~ Factor models~ Portfolio selection~ Shrinkage method. -Ledoit, Anderson Graduate School of Management, UCLA, USA; Wolf, Departamento de Estadistica y Econometria, Universidad Carlos ill de Madrid, Cl Madrid 126 28903 Getafe, Madrid, Spain, e-mail: mwolf@...





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