Prediction of Stock Market Index Using a Hybrid Technique of Artificial Neural Networks and Particle Swarm Optimization

Farnaz Ghashami, Kamyar Kamyar, S. Ali Riazi


In this paper we examine the ability of Artificial Neural Network methods (ANN) for predicting the stock market index. We first conduct an ANN analysis and then optimize the ANN model using Particle Swarm Optimization algorithm (PSO) to improve the prediction accuracy. In terms of data, we use NASDAQ index which is one of the most widely followed indices in the United States. Empirical results show that by determining the optimal set of biases and weights using PSO, we can augment the accuracy of the ANN model for this stock market data set.

Full Text:




  • There are currently no refbacks.

Paper Submission E-mail:

Applied Economics and Finance    ISSN 2332-7294 (Print)   ISSN 2332-7308 (Online)

Copyright © Redfame Publishing Inc.

To make sure that you can receive messages from us, please add the '' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders. If you have any questions, please contact: