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Sentiment Bias and Asset Prices: Evidence from Sports Betting Markets and Social Media

Author

Listed:
  • Arne Feddersen

    (University of Southern Denmark, Department of Environmental and Business Economics)

  • Brad Humphreys

    (West Virginia University, College of Business and Economics)

  • Brian Soebbing

    (Louisiana State University, School of Kinesiology)

Abstract

Previous research using attendance-based proxies for the number of investors with sentiment bias supported the presence of investor sentiment in sports betting markets. We use data from social media (Facebook \Likes") to proxy for participants with investor sentiment and analyze variation in prices set by bookmakers for evidence of influence from investor sentiment. Based on prices and outcomes over two seasons in seven professional sports leagues in Europe and North America, we develop new evidence that asset prices reflect the presence of investor sentiment in these markets, or that bookmakers believe they exist, by offering favorable betting lines for popular teams. Favorable prices do not translate into a higher probability of winning a bet.

Suggested Citation

  • Arne Feddersen & Brad Humphreys & Brian Soebbing, 2013. "Sentiment Bias and Asset Prices: Evidence from Sports Betting Markets and Social Media," Working Papers 13-07, Department of Economics, West Virginia University.
    • Handle: RePEc:wvu:wpaper:13-07
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    File URL: https://researchrepository.wvu.edu/cgi/viewcontent.cgi?article=1084&context=econ_working-papers
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    References listed on IDEAS

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    Cited by:

    1. Arne Feddersen & Brad R. Humphreys & Brian P. Soebbing, 2020. "Casual bettors and sentiment bias in NBA and NFL betting," Applied Economics, Taylor & Francis Journals, vol. 52(53), pages 5797-5806, November.
    2. Paul Bose & Eberhard Feess & Helge Mueller, 2022. "Favoritism towards High-Status Clubs: Evidence from German Soccer," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 38(2), pages 422-478.
    3. Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting," Working Papers 381, University of Zurich, Department of Business Administration (IBW).
    4. Lenten, Liam J.A. & Crosby, Paul & McKenzie, Jordi, 2019. "Sentiment and bias in performance evaluation by impartial arbitrators," Economic Modelling, Elsevier, vol. 76(C), pages 128-134.
    5. Michels, Rouven & Ötting, Marius & Langrock, Roland, 2023. "Bettors’ reaction to match dynamics: Evidence from in-game betting," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1118-1127.
    6. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    7. Barge-Gil, Andrés & García-Hiernaux, Alfredo, 2019. "Staking plans in sports betting under unknown true probabilities of the event," MPRA Paper 92196, University Library of Munich, Germany.
    8. Mills, Brian M. & Salaga, Steven, 2018. "A natural experiment for efficient markets: Information quality and influential agents," Journal of Financial Markets, Elsevier, vol. 40(C), pages 23-39.
    9. Andre Boik, 2017. "The empirical effects of competition on third‐degree price discrimination in the presence of arbitrage," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(4), pages 1023-1036, November.
    10. Christian Deutscher & Marius Ötting & Sandra Schneemann & Hendrik Scholten, 2019. "The Demand for English Premier League Soccer Betting," Journal of Sports Economics, , vol. 20(4), pages 556-579, May.
    11. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
    12. Christian Deutscher & Bernd Frick & Marius Ötting, 2018. "Betting market inefficiencies are short-lived in German professional football," Applied Economics, Taylor & Francis Journals, vol. 50(30), pages 3240-3246, June.
    13. David Winkelmann & Christian Deutscher, 2025. "Do Betting Markets Sense a Goal Coming? Evidence from the German Bundesliga," Papers 2505.21275, arXiv.org.
    14. Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    15. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    16. David Winkelmann & Christian Deutscher & Marius Ötting, 2021. "Bookmakers’ mispricing of the disappeared home advantage in the German Bundesliga after the COVID-19 break," Applied Economics, Taylor & Francis Journals, vol. 53(26), pages 3054-3064, June.
    17. Andrés Barge-Gil & Alfredo Garcia-Hiernaux, 2020. "Staking in Sports Betting Under Unknown Probabilities: Practical Guide for Profitable Bettors," Journal of Sports Economics, , vol. 21(6), pages 593-609, August.
    18. Georgios Nalbantis & Tim Pawlowski & Dennis Coates, 2017. "The Fans’ Perception of Competitive Balance and Its Impact on Willingness-to-Pay for a Single Game," Journal of Sports Economics, , vol. 18(5), pages 479-505, June.

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    JEL classification:

    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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