research-article

A combinatorial prediction market for the U.S. elections

Authors:

Miroslav Dudik,

Sebastien Lahaie,

David M. Pennock,

David RothschildAuthors Info & Claims

EC '13: Proceedings of the fourteenth ACM conference on Electronic commerce

Pages 341 - 358

https://doi.org/10.1145/2492002.2482601

Published: 16 June 2013 Publication History

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Abstract

We report on a large-scale case study of a combinatorial prediction market. We implemented a back-end pricing engine based on Dudik et al.'s (2012) combinatorial market maker, together with a wizard-like front end to guide users to constructing any of millions of predictions about the presidential, senatorial, and gubernatorial elections in the United States in 2012. Users could create complex combinations of predictions and, as a result, we obtained detailed information about the joint distribution and conditional estimates of election results. We describe our market, how users behaved, and how well our predictions compared with benchmark forecasts. We conduct a series of counterfactual simulations to investigate how our market might be improved in the future.

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Cited By

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Laskey KSun WHanson RTwardy CMatsumoto SGoldfedder B(2018)Graphical model market maker for combinatorial prediction marketsJournal of Artificial Intelligence Research10.1613/jair.1.1124963:1(421-460)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1613/jair.1.11249
Wah ELahaie SPennock D(2016)An empirical game-theoretic analysis of price discovery in prediction marketsProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060693(510-516)Online publication date: 9-Jul-2016
https://dl.acm.org/doi/10.5555/3060621.3060693
Chen YGhosh AKearns MRoughgarden TVaughan J(2016)Mathematical foundations for social computingCommunications of the ACM10.1145/296040359:12(102-108)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1145/2960403
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Index Terms

A combinatorial prediction market for the U.S. elections
1. Applied computing
  1. Law, social and behavioral sciences
    1. Economics

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Information

Published In

EC '13: Proceedings of the fourteenth ACM conference on Electronic commerce

June 2013

924 pages

ISBN:9781450319621

DOI:10.1145/2492002

General Chair:
Michael Kearns
University of Pennsylvania., USA
,
Program Chairs:
Preston McAfee
Google, USA
,
Éva Tardos
Cornell University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 June 2013

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EC '13

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SIGecom

EC '13: ACM Conference on Electronic Commerce

June 16 - 20, 2013

Pennsylvania, Philadelphia, USA

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EC '13 Paper Acceptance Rate 72 of 223 submissions, 32%;

Overall Acceptance Rate 664 of 2,389 submissions, 28%

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The 25th ACM Conference on Economics and Computation

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Cited By

View all

Laskey KSun WHanson RTwardy CMatsumoto SGoldfedder B(2018)Graphical model market maker for combinatorial prediction marketsJournal of Artificial Intelligence Research10.1613/jair.1.1124963:1(421-460)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1613/jair.1.11249
Wah ELahaie SPennock D(2016)An empirical game-theoretic analysis of price discovery in prediction marketsProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060693(510-516)Online publication date: 9-Jul-2016
https://dl.acm.org/doi/10.5555/3060621.3060693
Chen YGhosh AKearns MRoughgarden TVaughan J(2016)Mathematical foundations for social computingCommunications of the ACM10.1145/296040359:12(102-108)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1145/2960403
Dudík MFrongillo RVaughan J(2014)Market making with decreasing utility for informationProceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence10.5555/3020751.3020768(152-161)Online publication date: 23-Jul-2014
https://dl.acm.org/doi/10.5555/3020751.3020768

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A tractable combinatorial market maker using constraint generation

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