Establishing relationships among patterns in stock market data
Data & Knowledge Engineering
Reading the markets: forecasting public opinion of political candidates by news analysis
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Reassembling multilingual temporal news datasets with incomplete information
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Evaluating and understanding text-based stock price prediction models
Information Processing and Management: an International Journal
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NewsCATS is an Automated Text Categorization (ATC) prototype using a hand-made thesaurus to forecast intraday stock price trends from information contained in press releases. Due to a unique labeling approach and by carefully selecting the appropriate training data News- CATS achieves a performance which is clearly superior to other ATC prototypes used for stock price trend forecasting. In this paper we describe the architecture, training, and testing of NewsCATS as well as the results of an extensive robustness analysis.