2014/07/01 by Mithun Chakraborty, Chakraborty, Mithun, Sanmay Das +1
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #Consumer Market Behavior and Pricing #FOS: Computer and information sciences #Sports Analytics and Performance
paper · pdf · doi:10.48550/arxiv.1407.7015
openalex publication_date 2014/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Prediction markets are often used as mechanisms to aggregate information\nabout a future event, for example, whether a candidate will win an election.\nThe event is typically assumed to be exogenous. In reality, participants may\ninfluence the outcome, and therefore (1) running the prediction market could\nchange the incentives of participants in the process that creates the outcome\n(for example, agents may want to change their vote in an election), and (2)\nsimple results such as the myopic incentive compatibility of proper scoring\nrules no longer hold in the prediction market itself. We introduce a model of\ngames of this kind, where agents first trade in a prediction market and then\ntake an action that influences the market outcome. Our two-stage two-player\nmodel, despite its simplicity, captures two aspects of real-world prediction\nmarkets: (1) agents may directly influence the outcome, (2) some of the agents\ninstrumental in deciding the outcome may not take part in the prediction\nmarket. We show that this game has two different types of perfect Bayesian\nequilibria, which we term LPP and HPP, depending on the values of the belief\nparameters: in the LPP domain, equilibrium prices reveal expected market\noutcomes conditional on the participants' private information, whereas HPP\nequilibria are collusive -- participants effectively coordinate in an\nuninformative and untruthful way.\n