Pricing participating longevity-linked life annuities : a Bayesian Model Ensemble approach

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<title>Pricing participating longevity-linked life annuities</title>
<subTitle>: a Bayesian Model Ensemble approach</subTitle>
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<namePart>Bravo, Jorge Miguel</namePart>
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<abstract displayLabel="Summary">Participating longevity-linked life annuities (PLLA) in which benefits are updated periodically based on the observed survival experience of a given underlying population and the performance of the investment portfolio are an alternative insurance product offering consumers individual longevity risk protection and the chance to profit from the upside potential of financial market developments. This paper builds on previous research on the design and pricing of PLLAs by considering a Bayesian Model Ensemble of single population generalised age-period-cohort stochastic mortality models in which individual forecasts are weighted by their posterior model probabilities. For the valuation, we adopt a longevity option decomposition approach with risk-neutral simulation and investigate the sensitivity of results to changes in the asset allocation by considering a more aggressive lifecycle strategy. We calibrate models using Taiwanese (mortality, yield curve and stock market) data from 1980 to 2019. The empirical results provide significant valuation and policy insights for the provision of a cost effective and efficient risk pooling mechanism that addresses the individual uncertainty of death, while providing appropriate retirement income and longevity protection.

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<note type="statement of responsibility">Jorge Miguel Bravo</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20100065242">
<topic>Teorema de Bayes</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555016">
<topic>Longevidad</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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<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>06/06/2022 Volúmen 12 - Número 1 - junio 2022 , p. 125-159</text>
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