Technical Note—Ranking Distributions When Only Means and Variances Are Known
研究了在仅知均值和方差时如何排序分布，通过对边际效用变化施加约束来替代分布形状假设，为经济学、金融等领域的不确定性决策提供新方法。
In “Technical Note—Ranking Distributions When Only Means and Variances Are Known,” Müller, Scarsini, Tsetlin, and Winkler address the question of ranking distributions when only the first two moments—that is, means and variances—are known. This is important in decision making under uncertainty, with potential applications in economics, finance, statistics, and other areas. Previous results require some assumptions about the shape of the distributions, while this paper’s approach is to impose bounds on how much marginal utility can change, thus constraining risk preferences. Such a ranking is consistent with almost stochastic dominance and provides a new connection between the Sharpe and Omega ratios from finance.