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arXiv · 2504.19725

Analyzing distortion riskmetrics and weighted entropy for unimodal and symmetric distributions under partial information constraints

Baishuai Zuo·Chuancun Yin
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Abstract

In this paper, we develop the lower and upper bounds of worst-case distortion riskmetrics and weighted entropy for unimodal, and symmetric unimodal distributions when mean and variance information are available. We also consider the sharp upper bounds of distortion riskmetrics and weighted entropy for symmetric distribution under known mean and variance. These results are applied to (weighted) entropies, shortfalls and other risk measures. Specifically, entropies include cumulative Tsallis past entropy, cumulative residual Tsallis entropy of order {\alpha}, extended Gini coefficient, fractional generalized cumulative residual entropy, and fractional generalized cumulative entropy. Shortfalls include extended Gini shortfall, Gini shortfall, shortfall of cumulative residual entropy, and shortfall of cumulative residual Tsallis entropy. Other risk measures include nth-order expected shortfall, dual power principle and proportional hazard principle.

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Baishuai Zuo, Chuancun Yin. 2025-04-28. Analyzing distortion riskmetrics and weighted entropy for unimodal and symmetric distributions under partial information constraints. https://arxiv.org/abs/2504.19725

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