Development of Fuzzy Random Optimization Model Mean-Developing a fuzzy random portfolio optimization model Considering Investor's Risk Attitude
The purpose of this paper is to solve the stock selection problem for a portfolio with the least undesirable risk by solving the mathematical programming model in random fuzzy conditions. For considering the vague and uncertain environment of stock price rate of return, a mixed uncertainty procedure was applied. Also MAD was aaplied as the risk measure for optimizing the portfolio model. This research is based on the Mean-Absolute Deviation (MAD) model and assuming that the stock return is a fuzzy random variable, it considers the attitude of investors to risk in the form of risk-averse and risk-seeking investors and an efficient mathematical model for selecting Optimal portfolio are provided. Eventually, with the help of the genetic algorithm, an attempt was made to generate a quest for solving a given model. In the following, the Pareto optimal solutions are obtained according to the desired criteria, the optimal answer is obtained.
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