Portfolio Optimization Using Chance Constrained Compromise Programming

One of the key issues for investors is the issue of creating an optimal stock portfolio. In the issue of choosing an portfolio, the decision maker faces different and sometimes conflicting goals such as rate of return, liquidity, dividend, and risk. In portfolio optimization, the main issue is the optimal choice of assets and securities that can be made with a certain amount of capital, but on the one hand, the uncertainties associated with each share, and, on the other hand, the multiplicity of the optimal portfolio selection model, on the complexity of the problem increases. In this paper, the portfolio optimization under uncertainty has been studied. A randomized approach to converting uncertainty into a state of definiteness and agreeing to plan for a single objective is used in combination. Information about 20 pharmaceutical companies from the Tehran Stock Exchange has been used and the validity of the model has been investigated. The results show that the stock portfolio offered has a high performance.