Document Type : Research Paper

Authors

• Payam Hanafizadeh
• Abolfazl Jafari

Abstract

In this paper, a hybrid model of artificial neural networks is designed and used to evaluate the prediction ability of this hybrid model with individual Back Propagation feed forward. This study employs hybrid artificial neural networks consisting of Back Propagation and Kohonen Self Organizing Map (SOM) for better stock price prediction. Computational experience in predicting stock prices obtained from Tehran Stock Exchange reveals that the combination of Self Organizing Map and Back Propagation leads to better performance in comparison with the most popular individual Back Propagation feed forward networks.
JEL Classification: E37, C45, C51, C52, C53

Keywords

• Prediction
• Stock Price
• Self Organizing Map (SOM)
• feed forward Neural Networks