Article ID: | iaor20171930 |
Volume: | 18 |
Issue: | 2 |
Start Page Number: | 443 |
End Page Number: | 466 |
Publication Date: | Jun 2017 |
Journal: | Optimization and Engineering |
Authors: | Wu Dexiang, Kwon Roy |
Keywords: | optimization, decision, investment, simulation |
We consider a robust optimization approach for the problem of tracking a benchmark portfolio. A strict subset of assets are selected from the benchmark such that the expected return is maximized subject to both risk and tracking error limits. A robust version of the Fama‐French 3 factor model is developed whereby uncertatiny sets for the expected return and factor loading matrix are generated. The resulting model is a mixed integer second‐order conic problem. Computational results in tracking the S&P 100 out of sample show that the robust model can generate tracking portfolios that have better tracking error and Sharpe ratio than those generated by the nominal model.