Stock Price Forecasting by Combining News Mining and Time Series Analysis

被引：0

作者：

Tang, Xiangyu ^{[1
]}

Yang, Chunyu ^{[1
]}

Zhou, Jie ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Automat, State Key Lab Intelligent Technol & Syst, TNList, Beijing 10084, Peoples R China

来源：

2009 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 1 | 2009年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Stock price forecasting has aroused great concern in research of economy, machine learning and other fields. Time series analysis methods are usually utilized to deal with this task. In this paper, we propose to combine news mining and time series analysis to forecast inter-day stock prices. News reports are automatically analyzed with text mining techniques, and then the mining results are used to improve the accuracy of time series analysis algorithms. The experimental result on a half year Chinese stock market data indicates that the proposed algorithm can help to improve the performance of normal time series analysis in stock price forecasting significantly. Moreover, the proposed algorithm also performs well in stock price trend forecasting.

引用

页码：279 / 282

页数：4

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