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The “Large-Firm” Effect? Bettor Preferences And Market Prices In Ncaa Football

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  • Rodney Paul
  • Andrew P. Weinbach
  • Eric Higger

Abstract

NCAA football has a clear classification of “large” (AQ) and “small” (non-AQ) conferences. This setting lends itself to the testing of the “small-firm” effect found in financial markets in the college football betting market. The “small-firm” effect occurs when small cap firms outperform large cap firms; typically attributed to difficulty and costs in finding information on small firms. In college football, AQ-teams win more than implied by efficiency against non-AQ teams. At the same time, AQ teams receive a disproportionate share of bets on these games. The likely rationale behind these findings is the incentives created by the BCS system which leads the point spread to not be a true random variable within this market.

Suggested Citation

  • Rodney Paul & Andrew P. Weinbach & Eric Higger, 2013. "The “Large-Firm” Effect? Bettor Preferences And Market Prices In Ncaa Football," Journal of Prediction Markets, University of Buckingham Press, vol. 7(2), pages 29-41.
    • Handle: RePEc:buc:jpredm:v:7:y:2013:i:2:p:29-41
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    References listed on IDEAS

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    1. Stoll, Hans R. & Whaley, Robert E., 1983. "Transaction costs and the small firm effect," Journal of Financial Economics, Elsevier, vol. 12(1), pages 57-79, June.
    2. Rodney J. Paul & Andrew P. Weinbach, 2009. "Sportsbook Behavior in the NCAA Football Betting Market: Tests of the Traditional and Levitt Models of Sportsbook Behavior," Journal of Prediction Markets, University of Buckingham Press, vol. 3(2), pages 21-37, August.
    3. Roll, Richard, 1981. "A Possible Explanation of the Small Firm Effect," Journal of Finance, American Finance Association, vol. 36(4), pages 879-888, September.
    4. Barry, Christopher B. & Brown, Stephen J., 1984. "Differential information and the small firm effect," Journal of Financial Economics, Elsevier, vol. 13(2), pages 283-294, June.
    5. Rodney J. Paul & Andrew P. Weinbach & Patrick Coate, 2007. "Expectations and Voting in the NCAA Football Polls," Journal of Sports Economics, , vol. 8(4), pages 412-424, August.
    6. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    7. Rodney J. Paul & Andrew P. Weinbach, 2007. "Does Sportsbook.com Set Pointspreads to Maximize Profits? Tests of the Levitt Model of Sportsbook Behavior," Journal of Prediction Markets, University of Buckingham Press, vol. 1(3), pages 209-218, December.
    8. Steven D. Levitt, 2004. "Why are gambling markets organised so differently from financial markets?," Economic Journal, Royal Economic Society, vol. 114(495), pages 223-246, April.
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    Cited by:

    1. Randall W. Bennett, 2019. "Holdover Bias in the College Football Betting Market," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(1), pages 103-110, March.
    2. Evan Moore & James Francisco, 2019. "Efficiency, Profitability, and College Football: do Bettors Overrate the Major Conferences in Interconference Play?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 159-167, June.
    3. Justin Cox & Adam L. Schwartz & Bonnie F. Van Ness & Robert A. Van Ness, 2021. "The Predictive Power of College Football Spreads: Regular Season Versus Bowl Games," Journal of Sports Economics, , vol. 22(3), pages 251-273, April.

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    More about this item

    Keywords

    Efficient Markets; Betting Markets; Behavioral Finance;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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