Pricing anomalies threaten the value of prediction markets as a means of harnessing the ‘wisdom of the crowd’ to make accurate forecasts. The most persistent and puzzling pricing anomaly associated with price-implied prediction probabilities is the favourite-longshot bias (FLB). We demonstrate that existing models of the FLB fail to capture its full complexity, thereby preventing appropriate adjustments to market forecasts to improve their accuracy. We develop an agent-based model with heterogeneous agents in a fixed-odds market. Our agent-based simulations and comprehensive analysis using market data demonstrate that our model explains real market behaviour, including that of market makers, better than existing theories. Importantly, our results suggest that adequately complex models are necessary to describe complex phenomena such as pricing anomalies. We discuss how our model can be used to better understand the relation between market ecology and mispricing in contexts such as options and prediction markets, consequently enhancing their predictive power.
- OR in prediction markets
- Agent-based modelling
- Cognitive bias
- OR in sports
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- School of Informatics - Lecturer in Business Application of Informatics
- Artificial Intelligence and its Applications Institute
- Data Science and Artificial Intelligence
Person: Academic: Research Active