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Forecasting outcomes in spread betting markets: can bettors use 'quarbs' to beat the book?

Author

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  • David Paton

    (Nottingham University Business School, UK)

  • Leighton Vaughan Williams

    (Nottingham Trent University, UK)

Abstract

In this paper, we examine a relatively novel form of gambling, spread (or index) betting that overlaps with practices in conventional financial markets. In this form of betting, a number of bookmakers quote bid-offer spreads about the result of some future event. Bettors may buy (sell) at the top (bottom) end of a spread. We hypothesize that the existence of an outlying spread may provide uninformed traders with forecasting information that can be used to develop improved trading strategies. Using data from a popular spread betting market in the United Kingdom, we find that the price obtaining at the market mid-point does indeed provide a better forecast of asset values than that implied in the outlying spread. We further show that this information can be used to develop trading strategies leading to returns that are consistently positive and superior to those from noise trading. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • David Paton & Leighton Vaughan Williams, 2005. "Forecasting outcomes in spread betting markets: can bettors use 'quarbs' to beat the book?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 139-154.
    • Handle: RePEc:jof:jforec:v:24:y:2005:i:2:p:139-154
    DOI: 10.1002/for.949
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    References listed on IDEAS

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    Cited by:

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    2. Robin Maximilian Stetzka & Stefan Winter, 2023. "How rational is gambling?," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1432-1488, September.
    3. Benjamin Waggoner & Daniel Wines & Brian P. Soebbing & Chad S. Seifried & Jean Michael Martinez, 2014. "“Hot Hand” in the National Basketball Association Point Spread Betting Market: A 34-Year Analysis," IJFS, MDPI, vol. 2(4), pages 1-12, November.
    4. Marshall, Ben R., 2009. "How quickly is temporary market inefficiency removed?," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 917-930, August.
    5. S Lessmann & M-C Sung & J E V Johnson, 2011. "Towards a methodology for measuring the true degree of efficiency in a speculative market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2120-2132, December.
    6. Michael A. Smith & David Paton & Leighton Vaughan-Williams, 2004. "Costs, biases and betting markets: new evidence," Working Papers 2004/5, Nottingham Trent University, Nottingham Business School, Economics Division.
    7. David Paton & Donald S. Siegel & Leighton Vaughan Williams, 2009. "The Growth of Gambling and Prediction Markets: Economic and Financial Implications," Economica, London School of Economics and Political Science, vol. 76(302), pages 219-224, April.
    8. Bruno Deschamps, 2008. "Betting Markets Efficiency: Evidence From European Football," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(1), pages 66-76, May.
    9. Bruno Deschamps & Olivier Gergaud, 2007. "Efficiency in Betting Markets: Evidence from English Football," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 61-73, February.
    10. Sperb, Luis Felipe Costa & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2019. "Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 35(1), pages 321-335.
    11. Nikolaos Vlastakis & George Dotsis & Raphael N. Markellos, 2009. "How efficient is the European football betting market? Evidence from arbitrage and trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 426-444.
    12. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.

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