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Forecasting Intraday stock price trends with text mining techniques Mittermayer, M.-A. Inst. of Inf. Syst., Bern Univ., Switzerland;
This paper appears in: System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on Publication Date: 5-8 Jan. 2004 On page(s): 10 pp.- ISBN: 0-7695-2056-1 INSPEC Accession Number: 8883253 Digital Object Identifier: 10.1109/HICSS.2004.1265201 Date Published in Issue: 2004-02-26 10:51:29.0 Abstract 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.
