Mack's estimator motivated by large exposure asymptotics in a compound poisson setting

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<title>Mack's estimator motivated by large exposure asymptotics in a compound poisson setting</title>
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<namePart>Engler, Nils </namePart>
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<namePart>Filip Lindskog</namePart>
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<abstract displayLabel="Summary">The distribution-free chain ladder of Mack justified the use of the chain ladder predictor and enabled Mack to derive an estimator of conditional mean squared error of prediction for the chain ladder predictor. Classical insurance loss models, that is of compound Poisson type, are not consistent with Mack's distribution-free chain ladder. However, for a sequence of compound Poisson loss models indexed by exposure (e.g., number of contracts), we show that the chain ladder predictor and Mack's estimator of conditional mean squared error of prediction can be derived by considering large exposure asymptotics. Hence, quantifying chain ladder prediction uncertainty can be done with Mack's estimator without relying on the validity of the model assumptions of the distribution-free chain ladder</abstract>
<note type="statement of responsibility">Nils Engler, Filip Lindskog</note>
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<topic>Ciencias Actuariales y Financieras</topic>
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<topic>Mercado de seguros</topic>
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<topic>Reclamaciones</topic>
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<topic>Seguros</topic>
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<topic>Empresas de seguros</topic>
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<url displayLabel="electronic resource" usage="primary display">https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/macks-estimator-motivated-by-large-exposure-asymptotics-in-a-compound-poisson-setting/C1FC729CC7767F8B21F1AFD916E68C32</url>
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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>15/05/2024 Volumen 54 Número 2 - mayo 2024 , p. 310-326</text>
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