An Application of Pentagonal Neutrosophic Linear Programming for Stock Portfolio Optimization

Abstract

The Linear programming problems (LPP) have been widely applied to many real-world problems. In this study, a formulation of stock portfolio problem is proposed. The problem is formulated by involving neutrosophic pentagonal fuzzy numbers (NPFN) in the rate of risked return, expected return rate and portfolio risk amount. Based on score function, the problem is transformed to its corresponding crisp form. A solution algorithm is investigated to provide the
decision of the portfolio investment joined with investors in savings and securities. The main features of this study are: the investor can choose freely the risk coefficients to maximize the expected returns; also, the investors may determine their strategies under consideration of their own conditions. The optimal return rate is obtained by using TORA software. An example is introduced to indicate the efficiency and reliability of the technique.