Journal
COMPUTERS & OPERATIONS RESEARCH
Volume 38, Issue 9, Pages 1251-1258Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2010.10.020
Keywords
Investment; Linear programming; Robust optimization; Risk
Ask authors/readers for more resources
In this paper we develop a robust model for portfolio optimization. The purpose is to consider parameter uncertainty by controlling the impact of estimation errors on the portfolio strategy performance. We construct a simple robust mean absolute deviation (RMAD) model which leads to a linear program and reduces computational complexity of existing robust portfolio optimization methods. This paper tests the robust strategies on real market data and discusses performance of the robust optimization model empirically based on financial elasticity, standard deviation, and market condition such as growth, steady state, and decline in trend. Our study shows that the proposed robust optimization generally outperforms a nominal mean absolute deviation model. We also suggest precautions against use of robust optimization under certain circumstances. (C) 2010 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available