Sparse Mean-Variance Portfolios: a Penalized Utility Approach

• Activity Number: 604 - Recent Advances in High-Frequency and High-Dimensional Time Series
• Type: Topic Contributed
• Date/Time: Thursday, August 3, 2017 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): David Walker Puelz*
• Companies: University of Texas

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.