English, Article, Journal or magazine article edition: Improved Estimation of the Covariance Matrix of Stock Returns with an Application to Portofolio Selection Olivier Ledoit; Michael Wolf

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Bookmark: http://trove.nla.gov.au/version/154745
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Improved Estimation of the Covariance Matrix of Stock Returns with an Application to Portofolio Selection
Author
  • Olivier Ledoit
  • Michael Wolf
Physical Description
  • preprint
Notes
  • 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.
  • Covariance matrix estimation, factor models, portofolio selection, shrinkage
  • RePEc:upf:upfgen:586
Language
  • English
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