Information Aggregation in Dynamic Markets With Strategic Traders

Authors

  • Michael Ostrovsky

    1. Graduate School of Business, Stanford University, Stanford, CA 94305, U.S.A.; ostrovsky@gsb.stanford.edu
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    • I am grateful to Jeremy Bulow, Yeon-Koo Che, Peter DeMarzo, Yossi Feinberg, Emir Kamenica, Yair Livne, George Mailath, Konstantin Makarychev, Yury Makarychev, Stephen Morris, Sergey Norin, Marek Pycia, Philip Reny, Rahul Sami, Michael Schwarz, Costis Skiadas, Robert Wilson, Bumin Yenmez, and the co-editor and anonymous referees for helpful comments, suggestions, and discussions. I am grateful to the Hoover Institution for its hospitality during the year when the first draft of this paper was completed, and to the NSF for financial support.


Abstract

This paper studies information aggregation in dynamic markets with a finite number of partially informed strategic traders. It shows that, for a broad class of securities, information in such markets always gets aggregated. Trading takes place in a bounded time interval, and in every equilibrium, as time approaches the end of the interval, the market price of a “separable” security converges in probability to its expected value conditional on the traders' pooled information. If the security is “non-separable,” then there exists a common prior over the states of the world and an equilibrium such that information does not get aggregated. The class of separable securities includes, among others, Arrow–Debreu securities, whose value is 1 in one state of the world and 0 in all others, and “additive” securities, whose value can be interpreted as the sum of traders' signals.

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