Analysis of the effect of headline news in financial market through text categorisation

Satoru Takahashi, Hiroshi Takahashi, Kazuhiko Tsuda

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper, we analyse the relation between stock-price returns and Headline News. Headline News is a very important source of information in asset management and is sent in large quantities every day. We study the effect of more than 13,000 Headline News sent from Jiji Press. We classify Headline News into three types using text categorisation and analyse the reaction of a stock-price return to each types of news. From our research, we figure out following issues: (1) we make the text categorisation system that has about 80% of classification accuracy, (2) this system can extract effective information to stock-price returns from Headline News and (3) such information is more effective to the small firms.

Original languageEnglish
Pages (from-to)204-209
Number of pages6
JournalInternational Journal of Computer Applications in Technology
Volume35
Issue number2-4
DOIs
Publication statusPublished - 2009 Jun

Keywords

  • Headline news
  • Naïve bayes
  • Text auto categorisation
  • Text mining

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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