It takes all sorts: A heterogeneous agent explanation for prediction market mispricing

Authored by Valerio Restocchi, Frank McGroarty, Enrico Gerding, V Johnnie E Johnson

Date Published: 2018

DOI: 10.1016/j.ejor.2018.04.011

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

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. (C) 2018 Published by Elsevier B.V.

Tags

Agent-based modelling probability Risk Model Efficiency Forecasting Prices Prospect-theory Or in prediction markets Cognitive bias Or in sports Favorite-longshot bias State-contingent claims Betting market Bettors