Adaptive Neural Inference System (ANFIS) and Grid Matrix (GA) Strategies Approach in Optimizing the Investment Portfolio in Tehran Stock Exchange and OTC Iran

Subject Areas : Financial engineering

ALI SHEIDAEI NARMIGI ¹ , Fereydun Rahnama roodposhti ² , Reza Radfar ³

1 - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Received: 2020-10-18 Accepted : 2020-12-26 Published : 2022-09-23

Keywords: Genetic Algorithm, : Portfolio Optimization, Grid Analysis (GA) Adaptive Fuzzy Neural Inference System (ANFIS),

Abstract :

Portfolio optimization is a process in which the investor seeks to maximize return on investment or minimize risk. One of the main issues is to determine the optimization method, which is to form an optimal investment portfolio, which means minimizing investment risk and maximizing investment profit. The aim of this study was to investigate the capability of adaptive fuzzy neural inference system (ANFIS) and grid matrix (GA) strategies in selecting and optimizing the investment portfolio from among selected Tehran Stock Exchange and OTC companies. The grouping of stocks by the network matrix and the classification of companies based on their market value and the use of the law of quarters and finally their weighting is considered in proportion to the forecast return for the next month of that share. Also, a stock portfolio optimization model has been designed and presented using an adaptive fuzzy neural inference system and its combination with a genetic algorithm in which three different categories of time, technical and fundamental series variables are used as model inputs. It becomes. Research outputs show that these systems have the ability to optimize the stock portfolio.