Multi-period portfolio optimization model design with a new approach to fuzzy uncertainty

Portfolio optimization and selection is one of the most important issues in the financial world, so investors are trying to make decisions that are most in line with the real world. But the uncertainty in data and parameters, and the contradiction in the investor's goals, adds to the complexity of the stock portfolio optimization problem, and the other hand because of the efficient market, it is necessary to use multi-period models that, unlike single-period models, allow the investor to review their wealth at the beginning of each period. This paper introduces a new approach to optimizing a multi-period portfolio optimization based on fuzzy general theory and using scenario tree to deal with uncertainties. In addition to considering all of the above constraints, It has made it possible for the investor to be able to apply his manner by changing the parameter to optimistic-pessimistic, and there is no need to model in credibility, necessity or possibility mode. Then the proposed model is solved by the Epsilon constraint method. Finally, using the data of 17 companies from different industries operating in the Tehran Stock Exchange Market in 1398, we examine the validity of the model and its efficiency.