Portfolio optimization by using linear programing models based on genetic algorithm

4th International Conference on Operational Research

Sukono^1 ; Hidayat, Y.^2 ; Lesmana, E.^1 ; Putra, A.S.^1 ; Napitupulu, H.^1 ; Supian, S.^1

Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia^1

Department of Statisticss, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia^2

关键词: Efficient portfolio;    Genetic algorithm approach;    Investment portfolio;    Linear programing;    Linear programming algorithm;    Linear programming models;    Portfolio optimization;    Standard deviation;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/300/1/012001/pdf
DOI  :  10.1088/1757-899X/300/1/012001

来源: IOP

【 摘 要 】

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.