COMPARING THE EFFECTIVENESS OF ONE- AND TWO-STEP CONDITIONAL LOGIT MODELS FOR PREDICTING OUTCOMES IN A SPECULATIVE MARKET

Abstract

This paper compares two approaches to predicting outcomes in a speculative market, the horse race betting market. In particular, the nature of one-and two-step conditional logit procedures involving a process for exploding the choices et are outlined, their strengths and weaknesses are compared and the irrelative effectiveness is  evaluated by predicting winning probabilities for horse races at a UK racetrack. The models incorporate variables which are widely recognised as having predictive power and which should therefore be effectively discounted in market odds. Despite this handicap, both approaches produce probability estimates which can be used to earn positive returns, but the two-step approach yields substantially higher profits.