Applying Verbal Decision Making and Multi-objective Fuzzy Optimization Approach in Portfolio Selection

In this paper, some of the challenges of portfolio optimization are discussed simultaneously. So that the fuzzy multi-objective programming model was used to consider the multi-criteria nature of stock selection and the lack of correlation with the return on assets. Also, due to the weaknesses of traditional risk measures such as variance for risk assessment of the investor, the criterion of value at risk was replaced as a coherent risk criterion with the fuzzy credit theory approach. On the other hand, in this research, ZAPROS III method was used to interfere with investors' subjective opinions and judgments, and by considering the formal index of quality (FIQ), the views of investors in portfolio optimization were considered. In designing the model, in addition to the main constraints, limitations such as the minimum and maximum allocation of wealth to each asset, as well as the minimum and maximum number of stocks in the portfolio are considered. To demonstrate the applicability of the developed model, 10 of the more active companies accepted in Tehran Stock Exchange were used. The results of model implementation using the MOPSO algorithm showed that optimal pareto-optimized models of model execution compared to randomly assigned portfolios have better and more favorable performance in terms of achievement of predetermined goals.