Information Aggregation and Allocative Efficiency in Smooth Markets
研究了理性风险规避交易者如何在市场中通过交易逐步揭示私人信息，发现价格渐近平滑性（即小额买卖价格一致）能保证信息聚合和事后帕累托有效的资源配置，并证明基于成本函数的算法市场满足该条件。
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. This paper was accepted by Brad M. Barber, finance.