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In search of the source of informed trader information in the college football betting market

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Author Info

  • William Dare
  • John Gandar
  • Richard Zuber
  • Robert Pavlik
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    Abstract

    The movement between the opening and closing of betting lines on sports events has been shown to contain valuable information. The purpose of this study is to search for the source of this valuable information. Changes in college football betting lines are examined with respect to information from the widely disseminated Dunkel Index, the Associated Press Writers' Poll, and lagged performance variables. It is found that bettors use this information to bet but that this information is not significant to betting outcomes, which indicates noise trading. Most importantly, it is shown that the unexplained betting line movements are most important in explaining final game outcomes. This result leads to the conclusion that informed bettors are using private information.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310042000306961
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

    Volume (Year): 15 (2005)
    Issue (Month): 3 ()
    Pages: 143-152

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    Handle: RePEc:taf:apfiec:v:15:y:2005:i:3:p:143-152

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    References

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    1. Dare, William H. & MacDonald, S. Scott, 1996. "A generalized model for testing the home and favorite team advantage in point spread markets," Journal of Financial Economics, Elsevier, vol. 40(2), pages 295-318, February.
    2. Avery, Christopher & Chevalier, Judith, 1999. "Identifying Investor Sentiment from Price Paths: The Case of Football Betting," The Journal of Business, University of Chicago Press, vol. 72(4), pages 493-521, October.
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    Cited by:
    1. Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, Research Program on Forecasting.
    2. Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, Department of Economics, Research Program on Forecasting, revised Jan 2007.
    3. Baker, Rose D. & McHale, Ian G., 2013. "Forecasting exact scores in National Football League games," International Journal of Forecasting, Elsevier, vol. 29(1), pages 122-130.

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