IDEAS home Printed from https://ideas.repec.org/a/sae/jospec/v1y2000i2p177-186.html
   My bibliography  Save this article

The Search for Informed Traders in the Totals Betting Market for National Basketball Association Games

Author

Listed:
  • John M. Gandar

    (University of North Carolina at Charlotte)

  • Richard A. Zuber

    (University of North Carolina at Charlotte)

  • William H. Dare

    (Oklahoma State University)

Abstract

A recent article on line changes in the point spread betting market for National Basketball Association games found evidence that trading incorporates information into price. This article examines a closely related but previously unexamined betting market—the betting market for the total points scored in a game. The authors find that closing totals lines are more accurate forecasts of total points scored than are opening totals lines. It is shown that line changes move betting lines in the correct direction and by the appropriate magnitude to eliminate biases in opening totals lines. Line changes in this betting market, like those in the point spread betting market, cause prices to more accurately reflect fundamental values.

Suggested Citation

  • John M. Gandar & Richard A. Zuber & William H. Dare, 2000. "The Search for Informed Traders in the Totals Betting Market for National Basketball Association Games," Journal of Sports Economics, , vol. 1(2), pages 177-186, May.
  • Handle: RePEc:sae:jospec:v:1:y:2000:i:2:p:177-186
    DOI: 10.1177/152700250000100205
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/152700250000100205
    Download Restriction: no

    File URL: https://libkey.io/10.1177/152700250000100205?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hafer, R W & Hein, Scott E & MacDonald, S Scott, 1992. "Market and Survey Forecasts of the Three-Month Treasury-Bill Rate," The Journal of Business, University of Chicago Press, vol. 65(1), pages 123-138, January.
    2. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    3. repec:bla:jfinan:v:53:y:1998:i:1:p:385-401 is not listed on IDEAS
    4. repec:bla:jfinan:v:43:y:1988:i:4:p:995-1008 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    2. Kevin Krieger & Clay Girdner & Andy Fodor & David Kirch, 2013. "The Power Of Wagering On Power Conferences," Journal of Prediction Markets, University of Buckingham Press, vol. 7(1), pages 13-26.
    3. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    4. Berkowitz, Jason P. & Depken, Craig A. & Gandar, John M., 2015. "Information and accuracy in pricing: Evidence from the NCAA men׳s basketball betting market," Journal of Financial Markets, Elsevier, vol. 25(C), pages 16-32.
    5. 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.
    6. Jeremy Sandford & Paul Shea, 2013. "Optimal Setting of Point Spreads," Economica, London School of Economics and Political Science, vol. 80(317), pages 149-170, January.
    7. R. Alan Bowman & James Lambrinos & Thomas Ashman, 2013. "Competitive Balance in the Eyes of the Sports Fan," Journal of Sports Economics, , vol. 14(5), pages 498-520, October.
    8. Rodney J. Paul & Andrew P. Weinbach, 2008. "Line Movements and Market Timing in the Baseball Gambling Market," Journal of Sports Economics, , vol. 9(4), pages 371-386, August.
    9. Richard Borghesi, 2008. "Weather biases in the NFL totals market," Applied Financial Economics, Taylor & Francis Journals, vol. 18(12), pages 947-953.
    10. Štrumbelj, Erik & Vračar, Petar, 2012. "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting, Elsevier, vol. 28(2), pages 532-542.
    11. Baryla Jr., Edward A. & Borghesi, Richard A. & Dare, William H. & Dennis, Steven A., 2007. "Learning, price formation and the early season bias in the NBA," Finance Research Letters, Elsevier, vol. 4(3), pages 155-164, September.
    12. Frank Daumann & Markus Breuer, 2011. "The Role of Information in Professional Football and the German Football Betting Market," Chapters, in: Wladimir Andreff (ed.), Contemporary Issues in Sports Economics, chapter 6, Edward Elgar Publishing.

    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. Richard Deaves, 1996. "Forecasting Canadian Short-Term Interest Rates," Canadian Journal of Economics, Canadian Economics Association, vol. 29(3), pages 615-634, August.
    2. Jansen, Dennis W. & Kishan, Ruby Pandey, 1996. "An evaluation of federal reserve forecasting," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 89-109.
    3. Henry Bryant & Michael Haigh, 2004. "Bid-ask spreads in commodity futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(13), pages 923-936.
    4. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    5. Imad Moosa & Kelly Burns, 2014. "Error correction modelling and dynamic specifications as a conduit to outperforming the random walk in exchange rate forecasting," Applied Economics, Taylor & Francis Journals, vol. 46(25), pages 3107-3118, September.
    6. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    7. Zapata, Hector O. & Gil, Jose M., 1999. "Cointegration and causality in international agricultural economics research," Agricultural Economics, Blackwell, vol. 20(1), pages 1-9, January.
    8. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    9. Fullerton, Thomas M. & Kelley, Brian W., 2008. "El Paso Housing Sector Econometric Forecast Accuracy," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 40(1), pages 385-402, April.
    10. Ye, Haichun & Ashley, Richard & Guerard, John, 2015. "Comparing the effectiveness of traditional vs. mechanized identification methods in post-sample forecasting for a macroeconomic Granger causality analysis," International Journal of Forecasting, Elsevier, vol. 31(2), pages 488-500.
    11. Monticini, Andrea & Ravazzolo, Francesco, 2014. "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 304-315.
    12. Kunze, Frederik, 2017. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," University of Göttingen Working Papers in Economics 326, University of Goettingen, Department of Economics.
    13. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
    14. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
    15. Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A new monthly indicator of global real economic activity," Globalization Institute Working Papers 244, Federal Reserve Bank of Dallas.
    16. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    17. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    18. Li, Xue & Haslag, Joseph H., 2021. "On Phase Shifts In A New Keynesian Model Economy," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2080-2101, December.
    19. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    20. T. M. Fullerton & A. G. Walke, 2013. "Public transportation demand in a border metropolitan economy," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3922-3931, September.

    More about this item

    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:sae:jospec:v:1:y:2000:i:2:p:177-186. 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: SAGE Publications (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.