We explore whether, and to what extent, traders in a real world financial market, where participants’ judgements are reportedly well calibrated, are subject to duration misperception. To achieve this, we examine duration misperception in the horserace betting market. We develop a two-stage algorithm to predict horses’ winning probabilities that account for a duration-related factor that is known to affect horses’ winning prospects. The algorithm adapts survival analysis and combines it with the conditional logit model. Using a dataset of 4736 horseraces and the lifetime career statistics of the 53,295 horses running in these races, we demonstrate that prices fail to discount fully information related to duration since a horse's last win. We show that this failure is extremely costly, since a betting strategy based on the predictions arising from the model shows substantial profits (932.5 percent and 16.27 percent, with and without reinvestment of winnings, respectively). We discuss the important implications of duration neglect in the wider economy.
- OR in sports
- Cognitive bias
- Sports betting
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- School of Informatics - Personal Chair of Financial Computing (Risk Modelling)
- Artificial Intelligence and its Applications Institute
- Data Science and Artificial Intelligence
Person: Academic: Research Active