Information Aggregation and Allocative Efficiency in Smooth Markets

• 成果类型: Article
• 署名作者: Iyer, Krishnamurthy; Johari, Ramesh; Moallemi, Ciamac C.
• 署名单位: Cornell University; Stanford University; Columbia University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2014.1929
• 发表日期: 2014
• 页码: 2509-2524
• 关键词: Information aggregation; perfect Bayesian equilibrium; risk aversion

摘要

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 converge; furthermore, 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 functions (or, equivalently, markets based on market scoring rules) aggregate the information of traders.