Modeling and Forecasting Stock Prices Using an Artificial Neural Network and Imperialist Competitive Algorithm
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.
Volume (Year): 3 (2013)
Issue (Month): 1 (January)
|Contact details of provider:|| Web page: http://hrmars.com/index.php/pages/detail/Accounting-Finance-Journal|
When requesting a correction, please mention this item's handle: RePEc:hur:ijaraf:v:3:y:2013:i:1:p:296-302. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Hassan Danial Aslam)
If references are entirely missing, you can add them using this form.