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Modeling and Forecasting Stock Prices Using an Artificial Neural Network and Imperialist Competitive Algorithm

Author

Listed:
  • Hossein Rezaiedolatabadi

    () (University of Isfahan)

  • Saeed Sayadi

    () (Islamic Azad University)

  • Amirhossein Hosseini

    () (University of Isfahan)

  • Mohammadhossein Forghani

    () (University of Isfahan)

  • Morteza Shokhmgar

    () (University of Isfahan)

Abstract

In recent years, computer has become powerful tool for prediction of economical and financial variables. Different techniques of topics related to artificial intelligence, machine learning, and expert systems extended their place in the economic and financial issues that among these issues can refer to techniques of artificial neural networks, neural networks and fuzzy neural networks and Recurrent Neural Networks. In this paper, by using a hybrid model of multi-layer Perceptron artificial neural network and Imperialist competitive algorithm has been paid and present a method to predict stock price. The results of this implementation indicate a relatively high capacity hybrid model of artificial neural networks and Imperialist competitive algorithm to predict the stock market price of the Tehran Stock Exchange.

Suggested Citation

  • Hossein Rezaiedolatabadi & Saeed Sayadi & Amirhossein Hosseini & Mohammadhossein Forghani & Morteza Shokhmgar, 2013. "Modeling and Forecasting Stock Prices Using an Artificial Neural Network and Imperialist Competitive Algorithm," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 3(1), pages 296-302, January.
  • Handle: RePEc:hur:ijaraf:v:3:y:2013:i:1:p:296-302
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