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Journal of Financial Markets Vol. 68 2024

Price formation in field prediction markets: The wisdom in the crowd

Frederik Bossaerts1; Nitin Yadav2; Peter Bossaerts3; Chad Nash1; Torquil Todd1; Torsten Rudolf1; Rowena Hutchins1; Anne-Louise Ponsonby4; Karl Mattingly1

1 Dysrupt Labs, Melbourne, 3000, Victoria, Australia · 2 The University of Melbourne · 3 University of Cambridge · 4 Florey Institute of Neuroscience and Mental Health

open access

Abstract

Prediction markets are a successful information aggregation structure, however the exact mechanism by which private information is incorporated into the price remains poorly understood. We introduce a novel method based on the “Kyle model” to identify traders who contribute valuable information to the market price. Applied to a large field prediction market dataset, we identify traders whose trades have positive informational price impact. In contrast to others, these traders realize profit (on average) in excess of a theoretical expected informed lower bound. Results are replicated on other field prediction market datasets, providing strong evidence in favor of the Kyle model.

DOI
10.1016/j.finmar.2023.100881
Volume
68
Pages
100881
Language
en
Sources
crossref openalex

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