Daily stock market forecast from textual Web data

B. Wuthrich, Wing Sing Cho, S. Leung, D. Permunetilleke, K. Sankaran, J. Zhang, W. La

Research output: Journal article publicationConference articleAcademic researchpeer-review

108 Citations (Scopus)


A study was conducted to predict stock markets using information contained in articles published on the Web. Mostly textual articles appearing in the leading and influential financial newspapers were taken as input. From those articles, the daily closing values of major stock market indices in Asia, Europe and America were predicted. Textual statements contain not only the effect but also why it happened. Exploiting textual information in addition to numeric time series data increases the quality of the input. Hence, improved predictions are expected.
Original languageEnglish
Pages (from-to)2720-2725
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1 Dec 1998
Externally publishedYes
EventProceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, United States
Duration: 11 Oct 199814 Oct 1998

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering


Dive into the research topics of 'Daily stock market forecast from textual Web data'. Together they form a unique fingerprint.

Cite this