Economic Analysis of Horseracing Betting Markets

This thesis presents both empirical and theoretical studies on horseracing betting markets. The first two chapters mainly deal with the insider trading problem in the betting markets based on the Shin model (1993) and its extension (Jullien and Salanié (1994)) by employing a novel data set from Yorkshire racecourses during the 2013-2014 racing season. Apart from measuring the incidence of insider trading, we empirically test market efficiency. Our result demonstrates that the degree of insider trading based on the original Shin measure is slightly lower than the calculation based on its extension. We also find no evidence to confirm that the market is strongly efficient. The next chapter studies price-determining factors that affect the starting prices in the racing markets by utilising a unique cross-sectional and time series data set. We find strong evidence to suggest that the winning potential, the age of the horse, the weight the horse carries and the distance of the race are very significant factors in explaining the starting prices. Our findings also confirm that the condition of the turf, the size of the racecourse and the classification of the race have influences on the price. In the last chapter, we propose a theoretical model of how betting odds are adjusted by bookmakers in betting markets. We introduce the optimal stopping techniques into the betting literature for the first time through a two-horse simple benchmark model with both informed and uninformed noise punters. Our main finding shows that increased fraction of informed traders will initially lift the loss per trade to the bookmaker, but after reaching a certain point the loss declines. We also find out that as the fraction of noise traders goes up, the loss is incurred to learn, but the learning process is less informative and the costs are the same, so the decision of changing the prices for each horse is taken sooner