News Versus Sentiment: Predicting Stock Returns from News Stories
36 Pages Posted: 9 Jun 2016
Date Written: 2016-06
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.
Keywords: News, Text Analysis
JEL Classification: G12, G14
Suggested Citation: Suggested Citation