当只知道均值和方差时对分布进行排序

A. Müller, M. Scarsini, Ilia Tsetlin, R. L. Winkler
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引用次数: 5

摘要

在“技术笔记-仅知道均值和方差时的分布排序”中,m,斯卡尔西尼,Tsetlin和温克尔解决了仅知道前两个时刻即均值和方差时的分布排序问题。这在不确定情况下的决策中很重要,在经济学、金融学、统计学和其他领域都有潜在的应用。先前的结果需要对分布的形状进行一些假设,而本文的方法是对边际效用可以变化的程度施加限制,从而约束风险偏好。这样的排名与几乎随机的优势一致,并为金融业的夏普比率和欧米茄比率之间提供了一种新的联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ranking Distributions when only Means and Variances are Known
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.
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