Forecasting Intraday Stock Price Trends with Text Mining Techniques

Mittermayer, Marc-André (January 2004). Forecasting Intraday Stock Price Trends with Text Mining Techniques. Proceedings of the 37th Hawaii International Conference on System Sciences, 10 pp.. 10.1109/HICSS.2004.1265201

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In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Mittermayer, Marc-André

Subjects:

000 Computer science, knowledge & systems
300 Social sciences, sociology & anthropology > 330 Economics

Language:

English

Submitter:

Nicole Buys

Date Deposited:

20 Apr 2016 09:19

Last Modified:

26 Jun 2016 02:13

Publisher DOI:

10.1109/HICSS.2004.1265201

BORIS DOI:

10.7892/boris.79148

URI:

https://boris.unibe.ch/id/eprint/79148

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