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 long delayed reaction. Much of the delayed response to news occurs around the subsequent earnings announcement.

JEL Classification: G12, G14

Suggested Citation: Suggested Citation

Heston, Steven L. and Sinha, Nitish Ranjan, News Versus Sentiment: Predicting Stock Returns from News Stories (June, 2016). FEDS Working Paper No. 2016-48, Available at SSRN: https://ssrn.com/abstract=2792559 or http://dx.doi.org/10.17016/FEDS.2016.048