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News versus Sentiment : Predicting Stock Returns from News Stories

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Abstract

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.

Suggested Citation

  • Steven Heston & Nitish R. Sinha, 2016. "News versus Sentiment : Predicting Stock Returns from News Stories," Finance and Economics Discussion Series 2016-048, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2016-48
    DOI: 10.17016/FEDS.2016.048
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    Cited by:

    1. Bastian von Beschwitz & Donald B Keim & Massimo Massa, 2020. "First to “Read” the News: News Analytics and Algorithmic Trading," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(1), pages 122-178.
    2. Christina Bannier & Thomas Pauls & Andreas Walter, 2019. "Content analysis of business communication: introducing a German dictionary," Journal of Business Economics, Springer, vol. 89(1), pages 79-123, February.
    3. Donald B. Keim & Massimo Massa & Bastian von Beschwitz, 2018. "First to \"Read\" the News: New Analytics and Algorithmic Trading," International Finance Discussion Papers 1233, Board of Governors of the Federal Reserve System (U.S.).
    4. Ye, Jing & Xue, Minggao, 2021. "Influences of sentiment from news articles on EU carbon prices," Energy Economics, Elsevier, vol. 101(C).
    5. Carlini, Federico & Cucinelli, Doriana & Previtali, Daniele & Soana, Maria Gaia, 2020. "Don't talk too bad! stock market reactions to bank corporate governance news," Journal of Banking & Finance, Elsevier, vol. 121(C).
    6. Hillert, Alexander & Jacobs, Heiko & Müller, Sebastian, 2018. "Journalist disagreement," Journal of Financial Markets, Elsevier, vol. 41(C), pages 57-76.
    7. Mark Johnman & Bruce James Vanstone & Adrian Gepp, 2018. "Predicting FTSE 100 returns and volatility using sentiment analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 253-274, November.

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    More about this item

    Keywords

    News; Text Analysis;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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