THE APPLICATION OF RANKING PROBABILITY-MODELS TO RACETRACK BETTING

• 成果类型: Article; Proceedings Paper
• 署名作者: LO, VSY; BACONSHONE, J; BUSCHE, K
• 署名单位: University of Hong Kong; University of Hong Kong
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.41.6.1048
• 发表日期: 1995
• 页码: 1048-1059
• 关键词: RACETRACK BETTING; RUNNING TIME DISTRIBUTIONS; BETTING SYSTEMS

摘要

Hausch et al. (HZR) (1981) developed a betting system that demonstrated positive profits at two racetracks. The system assumes running times are distributed exponentially, but other distributions for running times (Henery 1981 and Stem 1990) have been shown to produce a better fit in Bacon-Shone et al. (1992a), Lo (1994), and Lo and Bacon-Shone (1994) using data from Hong Kong, the Meadowlands, and Japan. The better fit is at the cost of severely increased complexity in computing ranking probabilities, though. In response, Lo and Bacon-Shone (1992) proposed a simple model of computing ranking probabilities which closely approximates those based on the Henery and the Stern models and fits the data as well. This paper couples the Lo and Bacon-Shone model and the HZR system. For data sets from the United States and Hong Kong, we show improved profit over the HZR system at lower levels of risk using final betting data assuming zero computational costs. With data from Japan, our model shows little difference in profits from the HZR system.