Pareto-optimal peer-to-peer risk sharing with robust distortion risk measures

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<title>Pareto-optimal peer-to-peer risk sharing with robust distortion risk measures</title>
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<namePart>Zhu, Michael B.</namePart>
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<namePart>International Actuarial Association</namePart>
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<abstract displayLabel="Summary">They study Pareto optimality in a decentralized peer-to-peer risk-sharing market where agents' preferences are represented by robust distortion risk measures that are not necessarily convex. They obtain a characterization of Pareto-optimal allocations of the aggregate risk in the market, and we show that the shape of the allocations depends primarily on each agent's assessment of the tail of the aggregate risk. They quantify the latter via an index of probabilistic risk aversion, and we illustrate our results using concrete examples of popular families of distortion functions. As an application of our results, we revisit the market for flood risk insurance in the United States. They present the decentralized risk sharing arrangement as an alternative to the current centralized market structure, and we characterize the optimal allocations in a numerical study with historical flood data. They conclude with an in-depth discussion of the advantages and disadvantages of a decentralized insurance scheme in this setting</abstract>
<note type="statement of responsibility">Mario Ghossoub, Michael B. Zhu and Wing Fung Chong</note>
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<topic>Matemática del seguro</topic>
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<topic>Distribución de riesgos</topic>
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<topic>Peer to peer insurance</topic>
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<topic>Cálculo actuarial</topic>
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<topic>Inundaciones</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>15/09/2025 Volume 55 Issue 3 - September 2025 , p. 537 - 563</text>
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