A New approximation of annuity prices for age period cohort models

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<title>New approximation of annuity prices for age period cohort models</title>
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<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20240022181">
<namePart>Kapoor, Nikhil </namePart>
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<namePart>Sanders, Barbara </namePart>
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<dateIssued encoding="marc">2024</dateIssued>
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<abstract displayLabel="Summary">This letter presents a new general formula for estimating annuity prices within a wide range of stochastic mortality models. The formula is constructed using two building blocks: an approximation technique based on the WentzelKramersBrillouin method for calculating the sum of correlated lognormal random variables, and an approximate expression for the moment generating function of the lognormal distribution. Notably, this formula is applicable to virtually all ageperiodcohort models where period effects are represented by vector autoregressive models. This broad assumption encompasses the majority of existing stochastic mortality models in literature. Through a numerical illustration, we also demonstrate the reliability and precision of our new method in determining annuity prices</abstract>
<note type="statement of responsibility">Jean-François Bégin, Nikhil Kapoor & Bárbara Sanders </note>
<note>A Publisher Correction to this article was published </note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080573614">
<topic>Renta vitalicia</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080579258">
<topic>Cálculo actuarial</topic>
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<topic>Mortalidad</topic>
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<topic>Longevidad</topic>
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<title>European Actuarial Journal</title>
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<publisher>Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</publisher>
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<identifier type="local">MAP20220007085</identifier>
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<text>15/08/2024 Volumen 14 - Número 2 - agosto 2024 </text>
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<title> A New approximation of annuity prices for ageperiodcohort models</title>
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<identifier type="local">MAP20240016739</identifier>
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<namePart>Bégin, Jean-François</namePart>
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