Development of Optimal Stock Portfolio Selection Model in the Tehran Stock Exchange by Employing Markowitz Mean-Semivariance Model

Abstract

In an increasingly complex financial market, selecting the optimal stock portfolio has become a subject of intense debate. This study aims to develop a model for optimal stock portfolio selection. We apply Markowitz's mean-semivariance approach to determine the downside risk of portfolios, which reflects investors' intuitive perception of risk. In the first stage, the combination of the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with interval data is employed to identify and rank good quality stocks according to the recommended criteria by experts. After selecting qualified stocks, in the second phase, we create portfolios, and the weight invested in each stock is determined. Then, three portfolios are created for three groups of risk-averse, neutral to risk, and risk-taker investors. The mean-semivariance optimization model is used in this phase. The proposed approach in the paper is implemented in a real case study of the Tehran stock exchange (TSE). Three portfolios for three groups of investors were evaluated and compared to the market performance using sharp criteria. All three portfolios outperformed the market portfolio both in terms of risk and return. The proposed model of this study can be utilized as a decision support tool when forming an optimal stock portfolio by considering both experts’ opinions on stock evaluation and investor risk preferences simultaneously.