Information Aggregation and Allocative Efficiency in Smooth Markets

24 Pages Posted: 2 Apr 2010 Last revised: 1 Nov 2011

See all articles by Krishnamurthy Iyer

Krishnamurthy Iyer

University of Minnesota - Twin Cities - Department of Industrial and Systems Engineering

Ramesh Johari

Stanford University

Ciamac C. Moallemi

Columbia University - Columbia Business School, Decision Risk and Operations

Date Written: August 2, 2010

Abstract

Recent years have seen extensive investigation of the information aggregation properties of markets. However, relatively little is known about conditions under which a market will aggregate the private information of rational risk averse traders who optimize their portfolios over time; in particular, what features of a market encourage traders to ultimately reveal their private information through trades? We consider a market model involving finitely many informed risk-averse traders interacting with a market maker. Our main result identifies a basic asymptotic smoothness condition on prices in the market that ensures information is aggregated as long as portfolios remain bounded; further, under this assumption, the allocation achieved is ex post Pareto efficient. Asymptotic smoothness is fairly mild: it requires that, eventually, infinitesimal purchases or sales should see the same per unit price. Notably, we demonstrate that, under some mild conditions, algorithmic markets based on cost function (or, equivalently, markets based on market scoring rules) aggregate the information of traders.

Keywords: information aggregation, smooth markets, cost functions

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Suggested Citation

Iyer, Krishnamurthy and Johari, Ramesh and Moallemi, Ciamac C., Information Aggregation and Allocative Efficiency in Smooth Markets (August 2, 2010). Available at SSRN: https://ssrn.com/abstract=1581519 or http://dx.doi.org/10.2139/ssrn.1581519

Krishnamurthy Iyer

University of Minnesota - Twin Cities - Department of Industrial and Systems Engineering ( email )

111 Church St SE
Minneapolis, MN 55455
United States

Ramesh Johari (Contact Author)

Stanford University ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Ciamac C. Moallemi

Columbia University - Columbia Business School, Decision Risk and Operations ( email )

New York, NY
United States

HOME PAGE: http://moallemi.com/ciamac

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