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

Hossein Rezaiedolatabadi (ho.rezaie@gmail.com), Saeed Sayadi (saeed.sayadi@gmail.com), Amirhossein Hosseini (amir_3741@yahoo.com), Mohammadhossein Forghani (hoseinforghani_111@yahoo.com) and Morteza Shokhmgar (shokhmgarmorteza@yahoo.com)
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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

International Journal of Academic Research in Accounting, Finance and Management Sciences, 2013, vol. 3, issue 1, 296-302

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.

Keywords: Imperialist competitive algorithm; artificial neural networks; forecasting stock price; multi-layer perceptron (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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