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  • 标题:Analysis of Long-term Market Trend by Text-Mining of News Articles
  • 本地全文:下载
  • 作者:Takahisa Kuramoto ; Kiyoshi Izumi ; Yoshimura Shinobu
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2013
  • 卷号:28
  • 期号:3
  • 页码:291-296
  • DOI:10.1527/tjsai.28.291
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:In this study, we developed a new method of the long-term market analysis by using text-mining of news articles. Using our method, we conducted extrapolation tests to predict stock price averages by 19 industry and two market averages, TOPIX and Nikkei225 for about 10 years. As a result, 8 sectors in 21 sectors (about 40%) showed over about 60% accuracy, and 15 sectors in 21 sectors (over 70%) showed over about 55% accuracy. We also developed a web system of financial text-mining based on our method for financial professionals.
  • 关键词:text-mining ; stock prices prediction ; market trend ; UI
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