An integrated system based on fuzzy genetic algorithm and neural networks for stock price forecasting: Case study of price index of Tehran Stock Exchange
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 tre...
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| Veröffentlicht in: | The International journal of quality & reliability management 2014-01, Vol.31 (3), p.281-292 |
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| container_title | The International journal of quality & reliability management |
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| creator | Mousazadeh Abbassi, Noraddin Ali Aghaei, Mohammad Moradzadeh Fard, Mahdi |
| description | 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. |
| doi_str_mv | 10.1108/IJQRM-06-2012-0085 |
| format | Article |
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| subjects | Artificial intelligence Case studies Decision making Dow Jones averages Evolution Fuzzy logic Genetic algorithms Markets Mathematical models Methods Neural networks Nonlinearity Raw materials Securities markets Statistical analysis Stock exchanges Stock prices Time series Variables Wavelet transforms |
| title | An integrated system based on fuzzy genetic algorithm and neural networks for stock price forecasting: Case study of price index of Tehran Stock Exchange |
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