Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Trading on a Rigged Game: Outcome Manipulation in Prediction Markets / 158
Mithun Chakraborty, Sanmay Das

Prediction markets are popular mechanisms for aggregating information about a future event. In situations where market participants may significantly influence the outcome, running the prediction market could change the incentives of participants in the process that creates the outcome. We propose a new game-theoretic model that captures two aspects of real-world prediction markets: (1) agents directly affect the outcome the market is predicting, (2) some outcome-deciders may not participate in the market. We show that this game has two types of equilibria: When some outcome-deciders are unlikely to participate in the market, equilibrium prices reveal expected market outcomes conditional on participants' private information, whereas when all outcome-deciders are likely to participate, equilibria are collusive — agents effectively coordinate in an uninformative and untruthful way.