Forecasting methods are routinely employed to predict the outcome of competitive events (CEs) and to shed light on the factors that influence participants’ winning prospects (e.g., in sports events, political elections). Combining statistical models’ forecasts, shown to be highly successful...

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...

This paper introduces an improved approach for forecasting the outcome of horseraces. Building upon previous literature, a state-of-the-art modelling paradigm is developed which integrates least-square support vector regression and conditional logit procedures to predict horses' winning...

This paper examines the degree to which individuals tend to be overconfident in their judgements and identifies the implications for those trading in prediction markets. The findings from laboratory-based psychological studies of overconfidence are compared and contrasted with those from...

This paper compares two approaches to predicting outcomes in a speculative market, the horserace betting market. In particular, the nature of one- and two-step conditional logit procedures involving a process for exploding the choice set are outlined, their strengths and weaknesses are compared...

This paper explores differences in market ecology in a speculative financial market, the horserace betting market, and examines the impact these variations have on the information which returns seeking bettors need to incorporate in their subjective probability estimates. Conditional logit...

Accurately estimating the winning probabilities of participants in competitive events, such as elections and sports events, represents a challenge to standard forecasting frameworks such as regression or classification. They are not designed for modelling the competitive element, whereby a...