Probability models on horse-race outcomes
A number of models have been examined for modelling probability based on rankings. Most prominent among these are the gamma and normal probability models. The accuracy of these models in predicting the outcomes of horse races is investigated in this paper. The parameters of these models are estimated by the maximum likelihood method, using the information on win pool fractions. These models are used to estimate the probabilities that race entrants finish second or third in a race. These probabilities are then compared with the corresponding objective probabilities estimated from actual race outcomes. The data are obtained from over 15 000 races. it is found that all the models tend to overestimate the probability of a horse finishing second or third when the horse has a high probability of such a result, but underestimate the probability of a horse finishing second or third when this probability is low.
Volume (Year): 25 (1998)
Issue (Month): 2 ()
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References listed on IDEAS
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- Donald B. Hausch & William T. Ziemba & Mark Rubinstein, 1981. "Efficiency of the Market for Racetrack Betting," Management Science, INFORMS, vol. 27(12), pages 1435-1452, December.
- Ali, Mukhtar M, 1979. "Some Evidence of the Efficiency of a Speculative Market," Econometrica, Econometric Society, vol. 47(2), pages 387-92, March.
- Snyder, Wayne W, 1978. "Horse Racing: Testing the Efficient Markets Model," Journal of Finance, American Finance Association, vol. 33(4), pages 1109-18, September.
- Asch, Peter & Malkiel, Burton G. & Quandt, Richard E., 1982. "Racetrack betting and informed behavior," Journal of Financial Economics, Elsevier, vol. 10(2), pages 187-194, July.
- Dowie, Jack A, 1976. "On the Efficiency and Equity of Betting Markets," Economica, London School of Economics and Political Science, vol. 43(17), pages 139-50, May.
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