有界套利与近似理性行为
Bounded arbitrage and nearly rational behavior
AI总结：
本文建立了几乎无套利机会与近似理性决策的等价性，并应用于概率意见聚合和随机选择函数，分别给出有界套利原则与近似帕累托条件的等价性及对随机理性公理的弱化，提供距离上界。
摘要：
我们建立了几乎不存在套利机会的原则与近似理性决策之间的等价性。该原则的影响在概率意见的聚合和随机选择函数的背景下被考虑。在前者中，一个有界套利原则及其作为近似帕累托条件的等价形式被证明能够限制一组状态的集体概率评估与对个体评估的线性聚合规则之间的差异。在后者中，我们表明我们的一般有限套利机会原则转化为对麦克法登-里希特随机理性公理的弱化，并给出了一个随机选择函数到随机效用最大化模型类别中另一个函数的最小距离的上界。
英文摘要：
We establish the equivalence between a principle of almost absence of arbitrage opportunities and nearly rational decision-making. The implications of such principle are considered in the context of the aggregation of probabilistic opinions and of stochastic choice functions. In the former a bounded arbitrage principle and its equivalent form as an approximately Pareto condition are shown to bound the difference between the collective probabilistic assessment of a set of states and a linear aggregation rule on the individual assessments. In the latter we show that our general principle of limited arbitrage opportunities translates into a weakening of the McFadden-Richter axiom of stochastic rationality, and gives an upper bound for the minimum distance of a stochastic choice function to another in the class of random utility maximization models.
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