Faculty of Economics and Business Administration Publications Database

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

ISSN-Print: 0073-1129
Link External Source: Online Version
Year: 2012

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 financerelated word lists for sentiment analysis instead of a generic dictionary.