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News vs. Sentiment: Predicting Stock Returns from News Stories

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  • Steven L. Heston
  • Nitish Ranjan Sinha

Abstract

The authors used a dataset of more than 900,000 news stories to test whether news can predict stock returns. They measured sentiment with a proprietary Thomson Reuters neural network and found that daily news predicts stock returns for only one to two days, confirming previous research. Weekly news, however, predicts stock returns for one quarter. Positive news stories increase stock returns quickly, but negative stories receive a long-delayed reaction. Much of the delayed response to news occurs around the subsequent earnings announcement. Disclosure: The authors report no conflicts of interest. Editor’s Note Submitted 10 November 2015 Accepted 28 December 2016 by Stephen J. Brown

Suggested Citation

  • Steven L. Heston & Nitish Ranjan Sinha, 2017. "News vs. Sentiment: Predicting Stock Returns from News Stories," Financial Analysts Journal, Taylor & Francis Journals, vol. 73(3), pages 67-83, July.
    • Handle: RePEc:taf:ufajxx:v:73:y:2017:i:3:p:67-83
    DOI: 10.2469/faj.v73.n3.3
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