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Noise and Aggregation of Information in Large Markets

Authors: Diego García; Branko Urosevic;

Noise and Aggregation of Information in Large Markets

Abstract

We study a novel class of noisy rational expectations equilibria in markets with large number of agents. We show that, as long as noise increases with the number of agents in the economy, the limiting competitive equilibrium is well-defined and leads to non-trivial information acquisition, perfect information aggregation, and partially revealing prices, even if per capita noise tends to zero. We find that in such equilibrium risk sharing and price revelation play dierent roles than in the standard limiting economy in which per capita noise is not negligible. We apply our model to study information sales by a monopolist, information acquisition in multi-asset markets, and derivatives trading. The limiting equilibria are shown to be perfectly competitive, even when a strategic solution concept is used.

Country
Spain
Keywords

Partially revealing equilibria, competitive equilibrium, rational expectations, information acquisition, markets for information, derivatives trading, multi-asset markets, share auctions, multi-asset markets, derivatives trading, markets for information, share auctions, information acquisition, rational expectations, partially revealing equilibria, Finance and Accounting, competitive equilibrium, jel: jel:D82, jel: jel:G14

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    15
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Average
Green
hybrid