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Tail Moments of Compound Distributions

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<title>Tail Moments of Compound Distributions</title>
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<dateIssued encoding="marc">2022</dateIssued>
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<abstract displayLabel="Summary">In this article, we study the moment transform of both univariate and multivariate compound sums. We first derive simple explicit formulas for the first and second moment transforms when the (loss) frequency distribution is in the so-called (a,b,0) class. Then we show that the derived formulas can be used to efficiently compute risk measures such as the tail conditional expectation (TCE), the tail variance (TV), and higher tail moments. The results generalize those in Denuit (North American Actuarial Journal, 24 (4):51232, 2020).</abstract>
<note type="statement of responsibility">Jiandong Ren</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080579258">
<topic>Cálculo actuarial</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080620752">
<topic>Variables macro-económicas</topic>
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<title>North American actuarial journal</title>
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<publisher>Schaumburg : Society of Actuaries, 1997-</publisher>
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<identifier type="issn">1092-0277</identifier>
<identifier type="local">MAP20077000239</identifier>
<part>
<text>12/09/2022 Tomo 26 Número 3 - 2022 , p. 336-350</text>
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