Applying Data Mining Techniques for the Stock Price Prediction

被引：0

作者：

Wang Ying ^{[1
]}

Zhou Yan ^{[2
]}

Qi Fei ^{[2
]}

Zhang Haifeng ^{[2
]}

机构：

[1] China Univ Min & Technol, Sch Management, Beijing, Peoples R China

[2] China Univ Min & Technol, Sch Management, Financial Engn, Beijing, Peoples R China

来源：

INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS | 2014年 / 52卷 / 06期

关键词：

Data mining; stock price prediction; Principal component analysis; BP artificial neural networks;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This research aims to provide intelligent tool to predict stock price which shall provide service for the investment decision-making of stock traders. The data sets of Beijing Shougang Company from 2012 to 2013 were employed for the analysis and prediction as sample data. The combined model of principal component analysis algorithm and BP artificial neural networks algorithm were established. At last, we got the predicted stock price of Beijing Shougang Company from 2012 to 2013 by using the built model and prepared data. The predicted stock price was used to compare with the real value of stock price. The comparison indicated that data mining technique is an appropriate and sufficiently sensitive method to predict stock price.

引用

页码：116 / 129

页数：14

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