Stochastic dominance for linear combinations of infinite-mean risks

Abstract We establish a sufficient condition for comparing linear combinations of independent and identically distributed infinite-mean random variables under the usual stochastic order. We introduce a new class of distributions that includes many commonly used heavy-tailed models and show that within this class, a linear combination of random variables is stochastically larger when its weight vector is smaller in the sense of majorization order. We proceed to study the case where each random variable is a compound Poisson sum and demonstrate that if the stochastic dominance relation holds, the summand of the compound Poisson sum belongs to our new class of distributions. Additional discussions are presented for stable distributions.

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Publication Details

Journal
Journal of Applied Probability
Published
2026-09-30
DOI
https://doi.org/10.1017/jpr.2026.10138
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Stochastic dominance for linear combinations of infinite-mean risks

Taizhong Hu, Zhenfeng Zou, Seva Shneer, Yuyu Chen
Journal of Applied Probability
Risk and Portfolio Optimization
article

Stochastic dominance for linear combinations of infinite-mean risks

Taizhong Hu, Zhenfeng Zou, Seva Shneer, Yuyu Chen
article en

Abstract

Abstract We establish a sufficient condition for comparing linear combinations of independent and identically distributed infinite-mean random variables under the usual stochastic order. We introduce a new class of distributions that includes many commonly used heavy-tailed models and show that within this class, a linear combination of random variables is stochastically larger when its weight vector is smaller in the sense of majorization order. We proceed to study the case where each random variable is a compound Poisson sum and demonstrate that if the stochastic dominance relation holds, the summand of the compound Poisson sum belongs to our new class of distributions. Additional discussions are presented for stable distributions.

Journal of Applied Probability
University of Science and Technology of China (CN), The University of Melbourne (AU), Heriot-Watt University (GB)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 99%
Risk and Portfolio Optimization
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Stochastic dominance for linear combinations of infinite-mean risks — Taizhong Hu, Zhenfeng Zou, et al. · Journal of Applied Probability (2026) | TGRS Research Map | TGRS