Table of Contents
ISRN Applied Mathematics
Volume 2013, Article ID 570950, 9 pages
Research Article

CVaR Robust Mean-CVaR Portfolio Optimization

Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Namjoo Street, P.O. Box 1914, Rasht, Iran

Received 16 July 2013; Accepted 16 August 2013

Academic Editors: X. Liu and Q. Song

Copyright © 2013 Maziar Salahi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One of the most important problems faced by every investor is asset allocation. An investor during making investment decisions has to search for equilibrium between risk and returns. Risk and return are uncertain parameters in the suggested portfolio optimization models and should be estimated to solve the problem. However, the estimation might lead to large error in the final decision. One of the widely used and effective approaches for optimization with data uncertainty is robust optimization. In this paper, we present a new robust portfolio optimization technique for mean-CVaR portfolio selection problem under the estimation risk in mean return. We additionally use CVaR as risk measure, to measure the estimation risk in mean return. To solve the model efficiently, we use the smoothing technique of Alexander et al. (2006). We compare the performance of the CVaR robust mean-CVaR model with robust mean-CVaR models using interval and ellipsoidal uncertainty sets. It is observed that the CVaR robust mean-CVaR portfolios are more diversified. Moreover, we study the impact of the value of confidence level on the conservatism level of a portfolio and also on the value of the maximum expected return of the portfolio.