Parameter Uncertainty in Portfolio Selection: Shrinking the Inverse Covariance Matrix

Kourtis, Apostolos, Dotsis, George and Markellos, Raphael (2012) Parameter Uncertainty in Portfolio Selection: Shrinking the Inverse Covariance Matrix. Journal of Banking and Finance, 36 (9). pp. 2522-2531. ISSN 1872-6372

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Abstract

The estimation of the inverse covariance matrix plays a crucial role in optimal portfolio choice. We propose a new estimation framework that focuses on enhancing portfolio performance. The framework applies the statistical methodology of shrinkage directly to the inverse covariance matrix using two non-parametric methods. The first minimises the out-of-sample portfolio variance while the second aims to increase out-of-sample risk-adjusted returns. We apply the resulting estimators to compute the minimum variance portfolio weights and obtain a set of new portfolio strategies. These strategies have an intuitive form which allows us to extend our framework to account for short-sale constraints, high transaction costs and singular covariance matrices. A comparative empirical analysis against several strategies from the literature shows that the new strategies generally offer higher risk-adjusted returns and lower levels of risk.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Related URLs:
Depositing User: Elle Green
Date Deposited: 28 Aug 2012 16:43
Last Modified: 21 Mar 2019 12:54
URI: https://ueaeprints.uea.ac.uk/id/eprint/39461
DOI: 10.2139/ssrn.1343502

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