An integrated system based on fuzzy genetic algorithm and neural networks for stock price forecasting: Case study of price index of Tehran Stock Exchange
International Journal of Quality & Reliability Management
ISSN: 0265-671X
Article publication date: 25 February 2014
Abstract
Purpose
The aim of this research is to predict the total stock market index of the Tehran Stock Exchange, using the compound method of fuzzy genetics and neural network, in order for the active participants of the finance market as well as macro decision makers to be able to predict the market trend.
Design/methodology/approach
First, the prediction was done by neural network, then the output weight of optimum neural network was taken as standard to repeat this prediction using the genetic algorithm, and then the extracted pattern from the neural network was stated through discernible rules using fuzzy theory.
Findings
The main attention of this paper is investors and traders to achieve a method for predicting the stock market. Concerning the results of previous research, which confirms the relative superiority of non-linear models in price index prediction, an appropriate model has been offered in this research by compounding the non-linear method such as fuzzy genetics and neural network. The results indicate superiority of the designed system in predicting price index of the Tehran Stock Exchange.
Originality/value
This paper states its originality and value by compounding the non-linear method issues pattern to predict stock market, to encourage further investigation by academics and practitioners in the field.
Keywords
Citation
Mousazadeh Abbassi, N., Ali Aghaei, M. and Moradzadeh Fard, M. (2014), "An integrated system based on fuzzy genetic algorithm and neural networks for stock price forecasting: Case study of price index of Tehran Stock Exchange", International Journal of Quality & Reliability Management, Vol. 31 No. 3, pp. 281-292. https://doi.org/10.1108/IJQRM-06-2012-0085
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited