a1 Belk College of Business, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223. email@example.com
a2 Jones Graduate School of Business, Rice University, PO Box 2932, Houston, TX 77252. firstname.lastname@example.org
DeMiguel, Garlappi, and Uppal (2009) report that naïve diversification dominates mean-variance optimization in out-of-sample asset allocation tests. Our analysis suggests that this is largely due to their research design, which focuses on portfolios that are subject to high estimation risk and extreme turnover. We find that mean-variance optimization often outperforms naïve diversification, but turnover can erode its advantage in the presence of transaction costs. To address this issue, we develop 2 new methods of mean-variance portfolio selection (volatility timing and reward-to-risk timing) that deliver portfolios characterized by low turnover. These timing strategies outperform naïve diversification even in the presence of high transaction costs.
(Online publication January 20 2012)
We are thankful for comments from Nick Bollen, Stephen Brown (the editor), Jun Tu (the referee), and seminar participants at Rice University, Universidad Carlos III de Madrid, Georgia State University, the University of North Carolina at Charlotte, and the 2010 Conference on Financial Economics and Accounting.