News versus Sentiment: Predicting Stock Returns from News Stories

This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news, however, predicts stock returns for one quarter. Positive news stories increase stock returns quickly, but negative stories have a longdelayed reaction. Much of the delayed response to news occurs around the subsequent earnings announcement. Steven L. Heston and Nitish Ranjan Sinha. Heston: Department of Finance, Robert H. Smith School of Business, University of Maryland, College Park, [email protected]. Ranjan Sinha: Board of Governors of the Federal Reserve System, [email protected]. We thank Tim Loughran, Paul Tetlock, seminar participants at University of Maryland (finance brownbag), Acadian Asset Management and the Office of Financial Research. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. JEL–Classification: G12, G14