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Published in: Autonomous Agents and Multi-Agent Systems 2/2015

01-03-2015

Market manipulation with outside incentives

Authors: Yiling Chen, Xi Alice Gao, Rick Goldstein, Ian A. Kash

Published in: Autonomous Agents and Multi-Agent Systems | Issue 2/2015

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Abstract

Much evidence has shown that prediction markets can effectively aggregate dispersed information about uncertain future events and produce remarkably accurate forecasts. However, if the market prediction will be used for decision making, a strategic participant with a vested interest in the decision outcome may manipulate the market prediction to influence the resulting decision. The presence of such incentives outside of the market would seem to damage the market’s ability to aggregate information because of the potential distrust among market participants. While this is true under some conditions, we show that, if the existence of such incentives is certain and common knowledge, in many cases, there exist separating equilibria where each participant changes the market probability to different values given different private signals and information is fully aggregated in the market. At each separating equilibrium, the participant with outside incentives makes a costly move to gain trust from other participants. While there also exist pooling equilibria where a participant changes the market probability to the same value given different private signals and information loss occurs, we give evidence suggesting that two separating equilibria are more natural and desirable than many other equilibria of this game by considering domination-based belief refinement, social welfare, and the expected payoff of either participant in the game. When the existence of outside incentives is uncertain, however, trust cannot be established between players if the outside incentive is sufficiently large and we lose the separability at equilibria.

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Appendix
Available only for authorised users
Footnotes
1
Our results can be easily extended to a more general setting in which Bob’s private signal has a finite number \(n\) of realizations where \(n > 2\). However, it is non-trivial to extend our results to the setting in which Alice’s private signal has any finite number \(n\) of possible realizations. The reason is that our analysis relies on finding an interval for each of Alice’s signals, where the interval represents the range of reports that do not lead to a guaranteed loss for Alice when she receives this signal, and ranking all upper or lower endpoints of all such intervals. The number of possible rankings is exponential in \(n\), making the analysis challenging.
 
2
This assumption is often used to avoid the technical difficulties that PBE has for games with a continuum of strategies. See the work by Cho and Kreps [10] for an example.
 
3
There exist other separating PBE where Alice plays the same equilibrium strategies as in our characterization but Bob has different beliefs off the equilibrium path.
 
4
Situations with a convex \(Q(\cdot )\) function arise, for example, when manufactures have increasing returns to scale, which might be the case in our flu prediction example.
 
5
Bob’s belief can be different from that in \(SE_1\).
 
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Metadata
Title
Market manipulation with outside incentives
Authors
Yiling Chen
Xi Alice Gao
Rick Goldstein
Ian A. Kash
Publication date
01-03-2015
Publisher
Springer US
Published in
Autonomous Agents and Multi-Agent Systems / Issue 2/2015
Print ISSN: 1387-2532
Electronic ISSN: 1573-7454
DOI
https://doi.org/10.1007/s10458-014-9249-1

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