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Worst-case distortion risk measures of transformed losses with uncertain distributions lying in Wasserstein balls

 
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<title>Worst-case distortion risk measures of transformed losses with uncertain distributions lying in Wasserstein balls</title>
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<namePart>Liu, Fangda</namePart>
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<namePart>Yin, Mingren</namePart>
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<abstract displayLabel="Summary">This paper studies the worst-case distortion risk measures of the limited stop-loss transformtogether with its special cases, the stop-loss and limited loss transformswhen the underlying loss distribution is uncertain and lies within a general kkk-order Wasserstein ball around a reference distribution. We derive explicit expressions for these worst-case risk measures and identify the corresponding worst-case distributions. Our results also recover the findings of Guan et al. (2023) on worst-case stop-loss premiums under Wasserstein uncertainty. Numerical examples illustrate the worst-case distributions and risk measures, and we examine how the reference distribution, the Wasserstein ball radius, and the retention levels affect premiums for limited stop-loss reinsurance</abstract>
<note type="statement of responsibility">Jun Cai, Fangda Liu and Mingren Yin</note>
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<topic>Distribución de riesgos</topic>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>19/01/2026 Volume 56 Issue 1 - January 2026 , p.  270 - 294</text>
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