Sparse Mean-Variance Portfolios: A Penalized Utility Approach

24 Pages Posted: 10 Feb 2016 Last revised: 27 Dec 2016

David Puelz

University of Texas at Austin - Red McCombs School of Business

P. Richard Hahn

University of Chicago - Booth School of Business; University of Chicago - Booth School of Business - Econometrics and Statistics

Carlos M. Carvalho

University of Texas at Austin - Red McCombs School of Business

Date Written: February 8, 2016

Abstract

This paper considers mean-variance optimization under uncertainty, specifically when one desires a sparsified set of optimal portfolio weights. From the standpoint of a Bayesian investor, our approach produces a small portfolio from many potential assets while acknowledging uncertainty in asset returns and parameter estimates. We demonstrate the procedure using static and dynamic models for asset returns.

Keywords: portfolio optimization, passive investing, mean-variance optimization, decoupling shrinkage and selection

JEL Classification: C11, C61

Suggested Citation

Puelz, David and Hahn, P. Richard and Carvalho, Carlos M., Sparse Mean-Variance Portfolios: A Penalized Utility Approach (February 8, 2016). Available at SSRN: https://ssrn.com/abstract=2729504 or http://dx.doi.org/10.2139/ssrn.2729504

David Puelz (Contact Author)

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

P. Richard Hahn

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States

Carlos M. Carvalho

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

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