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Stock returns and investor sentiment: textual analysis and social media

Author

Listed:
  • Zachary McGurk

    (Canisus College)

  • Adam Nowak

    (West Virginia University)

  • Joshua C. Hall

    (West Virginia University)

Abstract

The behavioral finance literature has found that investor sentiment has predictive ability for equity returns. This differs from standard finance theory, which provides no role for investor sentiment. We examine the relationship between investor sentiment and stock returns by employing textual analysis on social media posts. We find that our investor sentiment measure has a positive and significant effect on abnormal stock returns. These findings are consistent across a number of different models and specifications, providing further evidence against non-behavioral theories.

Suggested Citation

  • Zachary McGurk & Adam Nowak & Joshua C. Hall, 2020. "Stock returns and investor sentiment: textual analysis and social media," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(3), pages 458-485, July.
    • Handle: RePEc:spr:jecfin:v:44:y:2020:i:3:d:10.1007_s12197-019-09494-4
    DOI: 10.1007/s12197-019-09494-4
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    2. Monica Martinez-Blasco & Vanessa Serrano & Francesc Prior & Jordi Cuadros, 2023. "Analysis of an event study using the Fama–French five-factor model: teaching approaches including spreadsheets and the R programming language," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-34, December.
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    More about this item

    Keywords

    Investor sentiment; Supervised learning; Stock returns; Social media; Sufficient reduction; Predictive regression;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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