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

Satoru Takahashi; Masakazu Takahashi; Hiroshi Takahashi; Kazuhiko Tsuda

doi:10.1007/11893004_40

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

Satoru Takahashi, Masakazu Takahashi, Hiroshi Takahashi, Kazuhiko Tsuda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings
Publisher	Springer Verlag
Pages	310-316
Number of pages	7
ISBN (Print)	3540465375, 9783540465379
DOIs	https://doi.org/10.1007/11893004_40
Publication status	Published - 2006
Externally published	Yes
Event	10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth, United Kingdom Duration: 2006 Oct 9 → 2006 Oct 11

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4252 LNAI - II
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
Country/Territory	United Kingdom
City	Bournemouth
Period	06/10/9 → 06/10/11

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11893004_40

Cite this

Takahashi, S., Takahashi, M., Takahashi, H., & Tsuda, K. (2006). Analysis of stock price return using textual data and numerical data through text mining. In Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings (pp. 310-316). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4252 LNAI - II). Springer Verlag. https://doi.org/10.1007/11893004_40

Analysis of stock price return using textual data and numerical data through text mining. / Takahashi, Satoru; Takahashi, Masakazu; Takahashi, Hiroshi et al.
Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings. Springer Verlag, 2006. p. 310-316 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4252 LNAI - II).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Takahashi, S, Takahashi, M, Takahashi, H & Tsuda, K 2006, Analysis of stock price return using textual data and numerical data through text mining. in Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4252 LNAI - II, Springer Verlag, pp. 310-316, 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, Bournemouth, United Kingdom, 06/10/9. https://doi.org/10.1007/11893004_40

Takahashi S, Takahashi M, Takahashi H, Tsuda K. Analysis of stock price return using textual data and numerical data through text mining. In Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings. Springer Verlag. 2006. p. 310-316. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11893004_40

Takahashi, Satoru ; Takahashi, Masakazu ; Takahashi, Hiroshi et al. / Analysis of stock price return using textual data and numerical data through text mining. Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings. Springer Verlag, 2006. pp. 310-316 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

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

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