IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-22-00065.html
   My bibliography  Save this article

Is herding efficient? Evidence from the college football point spread market

Author

Listed:
  • Alexander Traugutt

    (Elon University)

  • Jarid Morton

    (Western Kentucky University)

Abstract

This study examined the efficiency of herd behavior in the college football point spread market during the 2020-21 season, which was significantly impacted by the coronavirus pandemic. The virus caused chaos throughout the sport, which featured empty stadiums, infectious outbreaks, and scheduling disruptions. These uncertainties created an information gap, particularly regarding player availability, for sports bettors who utilize these types of data to build their models. As such, this market coupled with the pandemic backdrop provides an optimal setting to test the efficiency of herd behavior. Results indicated that the market was statistically inefficient, and from a herding standpoint, contrarian strategies resulted in win percentages that exceeded 50% for various probability cutoffs. This research presents applicable findings related to psychological factors that influence investor behavior, which can be generalized to markets within and outside of sport.

Suggested Citation

  • Alexander Traugutt & Jarid Morton, 2022. "Is herding efficient? Evidence from the college football point spread market," Economics Bulletin, AccessEcon, vol. 42(3), pages 1673-1680.
    • Handle: RePEc:ebl:ecbull:eb-22-00065
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2022/Volume42/EB-22-V42-I3-P139.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sean Wever & David Aadland, 2012. "Herd behaviour and underdogs in the NFL," Applied Economics Letters, Taylor & Francis Journals, vol. 19(1), pages 93-97, January.
    2. Gray, Philip K & Gray, Stephen F, 1997. "Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    3. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    4. repec:bla:jfinan:v:43:y:1988:i:4:p:995-1008 is not listed on IDEAS
    5. Bernheim, B Douglas, 1994. "A Theory of Conformity," Journal of Political Economy, University of Chicago Press, vol. 102(5), pages 841-877, October.
    6. Linda M. Woodland & Bill M. Woodland, 2015. "The National Football League season wins total betting market: The impact of heuristics on behavior," Southern Economic Journal, John Wiley & Sons, vol. 82(1), pages 38-54, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Corey A. Shank, 2018. "Is the NFL betting market still inefficient?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(4), pages 818-827, October.
    2. Quitzau, Jörn & Vöpel, Henning, 2009. "Der Faktor Zufall im Fußball: Eine empirische Untersuchung für die Saison 2007/08," HWWI Research Papers 1-22, Hamburg Institute of International Economics (HWWI).
    3. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    4. Kevin Krieger & Andy Fodor & Greg Stevenson, 2013. "The Sensitivity of Findings of Expected Bookmaker Profitability," Journal of Sports Economics, , vol. 14(2), pages 186-202, April.
    5. Yoon Tae Sung & Scott Tainsky, 2014. "The National Football League Wagering Market," Journal of Sports Economics, , vol. 15(4), pages 365-384, August.
    6. Gross, Johannes & Rebeggiani, Luca, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," MPRA Paper 87230, University Library of Munich, Germany.
    7. Andy Fodor, 2014. "Does Jet Lag Create A Profitable Opportunity For Nfl Bettors?," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 8(1), pages 41-52.
    8. Michael A. Roach, 2018. "Testing Labor Market Efficiency Across Position Groups in the NFL," Journal of Sports Economics, , vol. 19(8), pages 1093-1121, December.
    9. 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.
    10. Angie Andrikogiannopoulou & Filippos Papakonstantinou, 2018. "Individual Reaction to Past Performance Sequences: Evidence from a Real Marketplace," Management Science, INFORMS, vol. 64(4), pages 1957-1973, April.
    11. Corey A. Shank, 2019. "NFL betting market efficiency, divisional rivals, and profitable strategies," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 36(4), pages 567-580, September.
    12. Brian Hill, 2018. "Shadow and Spillover Effects of Competition in NBA Playoffs," Journal of Sports Economics, , vol. 19(8), pages 1067-1092, December.
    13. Michael DiFilippo & Kevin Krieger & Justin Davis & Andy Fodor, 2014. "Early Season NFL Over/Under Bias," Journal of Sports Economics, , vol. 15(2), pages 201-211, April.
    14. Tobias J. Moskowitz, 2021. "Asset Pricing and Sports Betting," Journal of Finance, American Finance Association, vol. 76(6), pages 3153-3209, December.
    15. Robert Arscott, 2023. "Market Efficiency and Censoring Bias in College Football Gambling," Journal of Sports Economics, , vol. 24(5), pages 664-689, June.
    16. Quitzau, Jörn, 2005. "Faktor Zufall als Spielverderber: zur Prognostizierbarkeit von Fußballergebnissen – Wettmärkte als effizienter Informationslieferant," Research Notes 18, Deutsche Bank Research.
    17. Sathya Ramesh & Ragib Mostofa & Marco Bornstein & John Dobelman, 2019. "Beating the House: Identifying Inefficiencies in Sports Betting Markets," Papers 1910.08858, arXiv.org, revised Oct 2019.
    18. Andrikogiannopoulou, Angie & Papakonstantinou, Filippos, 2017. "Individual reaction to past performance sequences: evidence from a real marketplace," LSE Research Online Documents on Economics 87997, London School of Economics and Political Science, LSE Library.
    19. Mark W. Nichols, 2014. "The Impact of Visiting Team Travel on Game Outcome and Biases in NFL Betting Markets," Journal of Sports Economics, , vol. 15(1), pages 78-96, February.
    20. Justin Davis & Andy Fodor & Luke McElfresh & Kevin Kreiger, 2015. "Exploiting Week 2 Bias in the NFL Betting Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 53-67.

    More about this item

    Keywords

    herd behavior; market efficiency; college football; sports betting; pandemic;
    All these keywords.

    JEL classification:

    • L8 - Industrial Organization - - Industry Studies: Services
    • G1 - Financial Economics - - General Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-22-00065. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.