Multi-Objective Possibility Model for Selecting the Optimal Stock Portfolio

In this paper, we utilize fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal, and triangular numbers in an optimal portfolio listed on the Tehran Stock Exchange. The aim is to maximize returns and minimize risk in order to find the optimal portfolio. Therefore, to achieve this goal, the problem of multi-objective nonlinear programming is addressed. Additionally, the mean-variance model and the standard mean deviation are substituted instead of the Markowitz mean-variance model to examine the selection of the optimal portfolio in the possible space. Finally, by calculating the possibility model of fuzzy numbers, we obtain the optimal stock portfolio, which can be used to construct the stock portfolio with the highest returns and the lowest risk.