Combinatorial Information Market Design
Information Systems Frontiers
Non-myopic strategies in prediction markets
Proceedings of the 9th ACM conference on Electronic commerce
Information aggregation in dynamic markets with strategic traders
Proceedings of the 10th ACM conference on Electronic commerce
Bluffing and strategic reticence in prediction markets
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Information aggregation in smooth markets
Proceedings of the 11th ACM conference on Electronic commerce
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We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, to evaluate the efficiency and speed of information aggregation, as well as test recent theoretical results on manipulative behavior by traders. We find that markets structured to have a fixed sequence of trades exhibit greater accuracy of information aggregation than the typical form that has unstructured trade. In comparing two commonly used mechanisms, we find no significant difference between the performance of the direct probability-report form and the indirect security-trading form of the market scoring rule. In the case of the markets with a structured order, we find evidence supporting the theoretical prediction that information aggregation is slower when information is complementary. In structured markets, the theoretical prediction that there will be more delayed trading in complementary markets is supported, but we find no support for the prediction that there will be more bluffing in complementary markets. However, the theoretical predictions are not borne out in the unstructured markets. This paper was accepted by Brad Barber, Teck Ho, and Terrance Odean, special issue editors.