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"Boom" or "Ruin"--Does It Make a Difference? Using Text Mining and Sentiment Analysis to Support Intraday Investment Decisions

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1 Author(s)
Siering, M. ; Goethe-Univ., Frankfurt, Germany

Investors have to deal with an increasing amount of information in order to make beneficial investment decisions. Thus, text mining is often applied to support the decision-making process by predicting the stock price impact of financial news. Recent research has shown that there exists a relation between news article sentiment and stock prices. However, this is not considered by previous text mining studies. In this paper, we develop a novel two-stage approach that connects text mining with sentiment analysis to predict the stock price impact of company-specific news. We find that the combination of text mining and sentiment analysis improves forecasting results. Additionally, a higher accuracy can be achieved by using finance-related word lists for sentiment analysis instead of a generic dictionary.

Published in:

System Science (HICSS), 2012 45th Hawaii International Conference on

Date of Conference:

4-7 Jan. 2012