In Defense of Portfolio Optimization: What If We Can Forecast?

David Allen, Colin Lizieri and Stephen Satchell

Financial Analysts Journal, 2019, vol. 75, issue 3, 20-38

Abstract: We challenge the academic consensus that estimation error makes mean–variance portfolio strategies inferior to passive equal-weighted approaches. We demonstrate analytically, via simulation, and empirically that investors endowed with modest forecasting ability benefit substantially from a mean–variance approach. An investor with some forecasting ability improves expected utility by increasing the number of assets considered. We frame our study realistically using budget constraints, transaction costs, and out-of-sample testing for a wide range of investments. We derive practical decision rules to choose between passive and mean–variance optimization and generate results consistent with much financial market practice and the original Markowitz formulation.Disclosure: The authors report no conflicts of interest. Editor’s Note:This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Nick Baltas was one of the reviewers for this article.Submitted 8 June 2018Accepted 20 March 2019 by Stephen J. Brown.

Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1080/0015198X.2019.1600958

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