An Efficient Learning System for Knowledge of Asset Management

Satoru Takahashi, Hiroshi Takahashi, Kazuhiko Tsuda

研究成果: Chapter

1 被引用数 (Scopus)

抄録

This paper examines if it is possible to obtain valuable knowledge for asset management by performing text mining on an enormous volume of analyst reports. Analyst reports are the evaluation reports of firms that are published by securities analysts. These reports describe the business conditions of firms mainly with a large amount of text information. However, it is impossible for a human being to read and understand all of the reports within a limited amount of time. To address this problem, we extract information from analyst reports automatically using text mining methods and analyze the influences of the reports. As a result of analyses, we confirm that the analyst reports contain valuable information that affect to stock prices. We also find that the stock prices react to the information before the report is published, which indicates that analysts are affected by the opinions of the other analysts.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編集者Mircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
出版社Springer Verlag
ページ494-500
ページ数7
ISBN(印刷版)9783540301325
DOI
出版ステータスPublished - 2004
外部発表はい

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)
3213
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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