Learning and Efficiency in a Gambling Market
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- Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
- Vaughan Williams, Leighton & Stekler, Herman O., 2010. "Sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 445-447, July.
- Coussement, Kristof & De Bock, Koen W., 2013.
"Customer churn prediction in the online gambling industry: The beneficial effect of ensemble learning,"
Journal of Business Research,
Elsevier, vol. 66(9), pages 1629-1636.
- K. Coussement & K.W. De Bock, 2013. "Customer Churn Prediction in the Online Gambling Industry: The Beneficial Effect of Ensemble Learning," Post-Print hal-00788063, HAL.
- Adi Schnytzer & Guy Weinberg, 2011. "Testing for Home Team and Favorite Biases in the Australian Rules Football Fixed Odds and Point Spread Betting Markets," Working Papers 2011-13, Bar-Ilan University, Department of Economics.
- Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
- Adi Schnytzer, 2011. "The Prediction Market for the Australian Football League," Working Papers 2011-15, Bar-Ilan University, Department of Economics.
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Keywordsmarket efficiency; optimal learning; Kalman filter;
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