Learning value-added information of asset management from analyst reports through text mining

Satoru Takahashi, Masakazu Takahashi, Hiroshi Takahashi, Kazuhiko Tsuda

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Text mining, one of the emerging fields of data mining, aims at acquiring useful knowledge from text data. In the asset management in finance task domain, although there exist various text data like accounting settlement or analysts' reports, few research and development have been conducted. In this paper, we will explore the feasibility to extract valuable knowledge for asset management through text mining using analyst reports as text data. We will analyze the relationship between text data and numerical data. From empirical study on the practical data, we have confirmed the effectiveness: (1) the extracted keywords are influential to the stock prices, (2) such information is more effective to the large-cap stocks, and (3) such keyword information become more valuable by using numerical information together.

本文言語English
ホスト出版物のタイトルKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
出版社Springer Verlag
ページ785-791
ページ数7
ISBN(印刷版)354028897X, 9783540288978
DOI
出版ステータスPublished - 2005
外部発表はい
イベント9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
継続期間: 2005 9 142005 9 16

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)
3684 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
CountryAustralia
CityMelbourne
Period05/9/1405/9/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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