عنوان مقاله [English]
Nowadays, the stock market is one of the common ways to invest money. Selection an appropriate portfolio is one of the main problems for investors. This paper proposes an integrated multi objective model for portfolio selection problem. The model is based on Markowitz mean-variance model. Markowitz model considered maximization of portfolio expected rate of return and minimization of portfolio risk. In the proposed model portfolio efficiency is considered in addition to portfolio return and portfolio risk simultaneity. The proposed model is a multiple objective programming model which maximizes return and efficiency and minimizes risk of the portfolio. Due to weaknesses of classic DEA model, the paper applies DEA cross-efficiency model to estimate efficiency. There are two problems of using simple cross-efficiency evaluation in portfolio selection. One of them is the lack of portfolio diversification. Under cross-efficiency evaluation, selecting DMUs which averagely perform well in all factors and excluding DMUs which perform well in only subset of factors is more likely. Due to this issue, a poor diversified portfolio will be selected which include similar DMUs. The other problem is the ganging-together phenomenon of cross-efficiency. Assume two DMUs have similar factor levels; hence they will use similar inputs and outputs weights. It is clear that two DMUs increase each others cross efficiency score and have more chance to win. On the contrary, a DMU which its factor levels are so different from other DMUs has lower chance of winning. The model is solved in two ways: using exact algorithm and using Non-dominated sorting genetic algorithm (NSGA-II) and the results are compared. To illustrate the performance of the proposed model, the actual data from 52 assets of Iran stock market is gathered and the results are compared with Markowitz model. The results showed that our proposed model increases portfolio efficiency in compared with Markowitz model while reduction of expected return is low.