A Novel Prediction Method for Stock Index Applying Grey Theory and Neural Networks

摘要：

This paper presents a better prediction model by the integration of neural network technique and grey theory for the stock index. In this paper, the grey theory applied include grey forecast model and grey relationship analysis. A GM(1, 1) grey forecast model was applied to predict the next days stock index. Grey relationship analysis was used to filter the most important quantitative technical indices. To examine the influence of dimension of the model to prediction accuracy, seven different kinds of dimension 5, 6, 8, 10, 12, 14, and15 were tested. The generated data were then regarded as new technical indices in grey relationship analysis and prediction of neural network.Finally, a Recurrent Neural Network was developed to train and predict the price trend of stock index. The conclusion shows our models can provide good prediction for this problem.

关键词： Stock Index GM(1, 1) Grey Relationship Analysis Recurrent Neural Network

作者: Shen Yan

作者单位: College of Science, Tianjin University of Technology, Tianjin, P.R. China

会议类型: 国际会议

会议名称: The Seventh International Symposium(ISORA08)(第七届国际效力研究及其应用学术会议)

会议地点: 云南丽江

会议语种:英文

页码: 104-111

在线出版日期: 2008-10-31（万方平台首次上网日期，不代表论文的发表时间）