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Finding profitable forecast combinations using probability scoring rules

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  • Grant, Andrew
  • Johnstone, David
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    Abstract

    This study examines the success of bets on Australian Football League (AFL) matches made by identifying panels of highly proficient forecasters and betting on the basis of their pooled opinions. The data set is unusual, in that all forecasts are in the form of probabilities. Bets are made "on paper"Â against quoted market betting odds according to the (fractional) Kelly criterion. To identify expertise, individual forecasters are scored using conventional probability scoring rules, a "Kelly score"Â representing the forecaster's historical paper profits from Kelly-betting, and the more simplistic "categorical score"Â (number of misclassifications). Despite implicitly truncating all probabilities to either 0 or 1 before evaluation, and thus losing a lot of information, the categorical scoring rule appears to be a propitious way of ranking probability forecasters. Bootstrap significance tests indicate that this improvement is not attributable to chance.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 26 (2010)
    Issue (Month): 3 (July)
    Pages: 498-510

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    Handle: RePEc:eee:intfor:v:26:y::i:3:p:498-510

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    Web page: http://www.elsevier.com/locate/ijforecast

    Related research

    Keywords: Probability scoring rule Kelly betting Kelly probability score Combining probability forecasts Economic forecast evaluation Probability football;

    References

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    1. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, School of Economics and Management, University of Aarhus.
    2. Roy Batchelor & Pami Dua, 1995. "Forecaster Diversity and the Benefits of Combining Forecasts," Management Science, INFORMS, vol. 41(1), pages 68-75, January.
    3. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    4. David Johnstone, 2007. "Economic Darwinism: Who has the Best Probabilities?," Theory and Decision, Springer, vol. 62(1), pages 47-96, February.
    5. repec:reg:rpubli:259 is not listed on IDEAS
    6. Michael P. Clements, 2004. "Evaluating the Bank of England Density Forecasts of Inflation," Economic Journal, Royal Economic Society, vol. 114(498), pages 844-866, October.
    7. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    8. Graham, John R, 1996. "Is a Group of Economists Better than One? Than None?," The Journal of Business, University of Chicago Press, vol. 69(2), pages 193-232, April.
    9. 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, 04.
    10. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 39-46, January.
    11. Allan Timmermann & Halbert White & Ryan Sullivan, 1998. "Data-Snooping, Technical Trading, Rule Performance and the Bootstrap," FMG Discussion Papers dp303, Financial Markets Group.
    12. MacLean, Leonard C. & Sanegre, Rafael & Zhao, Yonggan & Ziemba, William T., 2004. "Capital growth with security," Journal of Economic Dynamics and Control, Elsevier, vol. 28(5), pages 937-954, February.
    13. repec:reg:wpaper:259 is not listed on IDEAS
    14. L. C. MacLean & W. T. Ziemba & G. Blazenko, 1992. "Growth Versus Security in Dynamic Investment Analysis," Management Science, INFORMS, vol. 38(11), pages 1562-1585, November.
    15. Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Research Papers 1854, Stanford University, Graduate School of Business.
    16. Robert L. Winkler, 1986. "Expert Resolution," Management Science, INFORMS, vol. 32(3), pages 298-303, March.
    17. Kenneth C. Lichtendahl, Jr. & Robert L. Winkler, 2007. "Probability Elicitation, Scoring Rules, and Competition Among Forecasters," Management Science, INFORMS, vol. 53(11), pages 1745-1755, November.
    18. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    19. Jose, Victor Richmond R. & Winkler, Robert L., 2008. "Simple robust averages of forecasts: Some empirical results," International Journal of Forecasting, Elsevier, vol. 24(1), pages 163-169.
    20. Clemen, Robert T. & Murphy, Allan H. & Winkler, Robert L., 1995. "Screening probability forecasts: contrasts between choosing and combining," International Journal of Forecasting, Elsevier, vol. 11(1), pages 133-145, March.
    21. Yuming Li, 1993. "Growth-Security Investment Strategy for Long and Short Runs," Management Science, INFORMS, vol. 39(8), pages 915-924, August.
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    Cited by:
    1. Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2012. "A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction," European Journal of Operational Research, Elsevier, vol. 218(1), pages 163-174.
    2. 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.
    3. Adi Schnytzer, 2011. "The Prediction Market for the Australian Football League," Working Papers 2011-15, Department of Economics, Bar-Ilan University.

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