In Defense of Portfolio Optimization: What If We Can Forecast?. Issue 3 (1st July 2019) - Allen, David; Lizieri, Colin; Satchell, Stephen
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. Abstract : 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 2018 Accepted 20 March 2019 by Stephen J. Brown.