Analysis of stock price return using textual data and numerical data through text mining

Satoru Takahashi, Masakazu Takahashi, Hiroshi Takahashi, Kazuhiko Tsuda

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

In finance task domain, it is indispensable to get and analyze information as quickly as possible. Analyst's reports are one of the important information in asset management, and these include a large amount of text information. However, it is very difficult to handle text information of analyst's reports, few research and development have been conducted. In [5] and [6] we explored the feasibility to extract valuable knowledge for asset management through text mining using analyst's reports as text data. And we found the effectiveness of keyword information. In this paper we make further research of analyst's reports. From empirical study on the practical data, we have confirmed the effectiveness of using keyword information and numerical information together: (1) the effectiveness of keyword information is different by the direction of change of earning estimate; (2) the keyword of "Upward (or Downward) surprise in forecast" has strong effect to stock price return.

本文言語English
ホスト出版物のタイトルKnowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings
出版社Springer Verlag
ページ310-316
ページ数7
ISBN(印刷版)3540465375, 9783540465379
DOI
出版ステータスPublished - 2006
外部発表はい
イベント10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth, United Kingdom
継続期間: 2006 10 92006 10 11

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4252 LNAI - II
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
CountryUnited Kingdom
CityBournemouth
Period06/10/906/10/11

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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