Finding profitable forecast combinations using probability scoring rules
AbstractThis 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 InfoArticle provided by Elsevier in its journal International Journal of Forecasting.
Volume (Year): 26 (2010)
Issue (Month): 3 (July)
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Web page: http://www.elsevier.com/locate/ijforecast
Probability scoring rule Kelly betting Kelly probability score Combining probability forecasts Economic forecast evaluation Probability football;
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- Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010.
CREATES Research Papers
2010-21, School of Economics and Management, University of Aarhus.
- Justin Wolfers & Eric Zitzewitz, 2004.
NBER Working Papers
10504, National Bureau of Economic Research, Inc.
- Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Research Papers 1854, Stanford University, Graduate School of Business.
- Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Working paper 259, Regulation2point0.
- Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Discussion Papers 03-025, Stanford Institute for Economic Policy Research.
- 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.
- 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.
- Jose A. Lopez, 1995. "Evaluating the predictive accuracy of volatility models," Research Paper 9524, Federal Reserve Bank of New York.
- Allan Timmermann & Halbert White & Ryan Sullivan, 1998.
"Data-Snooping, Technical Trading, Rule Performance and the Bootstrap,"
FMG Discussion Papers
dp303, Financial Markets Group.
- Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
- Sullivan, Ryan & Timmermann, Allan G & White, Halbert, 1998. "Data-Snooping, Technical Trading Rule Performance and the Bootstrap," CEPR Discussion Papers 1976, C.E.P.R. Discussion Papers.
- 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.
- 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.
- 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.
- Roy Batchelor & Pami Dua, 1995. "Forecaster Diversity and the Benefits of Combining Forecasts," Management Science, INFORMS, vol. 41(1), pages 68-75, January.
- 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.
- 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.
- Yuming Li, 1993. "Growth-Security Investment Strategy for Long and Short Runs," Management Science, INFORMS, vol. 39(8), pages 915-924, August.
- 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.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- David Johnstone, 2007. "Economic Darwinism: Who has the Best Probabilities?," Theory and Decision, Springer, vol. 62(1), pages 47-96, February.
- 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.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- Robert L. Winkler, 1986. "Expert Resolution," Management Science, INFORMS, vol. 32(3), pages 298-303, March.
- Adi Schnytzer, 2011. "The Prediction Market for the Australian Football League," Working Papers 2011-15, Department of Economics, Bar-Ilan University.
- 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.
- 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.
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