کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
480910 | 1446148 | 2009 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Identifying winners of competitive events: A SVM-based classification model for horserace prediction Identifying winners of competitive events: A SVM-based classification model for horserace prediction](/preview/png/480910.png)
The aim of much horserace modelling is to appraise the informational efficiency of betting markets. The prevailing approach involves forecasting the runners’ finish positions by means of discrete or continuous response regression models. However, theoretical considerations and empirical evidence suggest that the information contained within finish positions might be unreliable, especially among minor placings. To alleviate this problem, a classification-based modelling paradigm is proposed which relies only on data distinguishing winners and losers. To assess its effectiveness, an empirical experiment is conducted using data from a UK racetrack. The results demonstrate that the classification-based model compares favourably with state-of-the-art alternatives and confirm the reservations of relying on rank ordered finishing data. Simulations are conducted to further explore the origin of the model’s success by evaluating the marginal contribution of its constituent parts.
Journal: European Journal of Operational Research - Volume 196, Issue 2, 16 July 2009, Pages 569–577