Pricing participating longevity-linked life annuities

Detalhes bibliográficos
Autor(a) principal: Bravo, Jorge Miguel
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/118506
Resumo: Bravo, J. M. (2022). Pricing participating longevity-linked life annuities: a Bayesian Model Ensemble approach. European Actuarial Journal, 12(1), 125-159. https://doi.org/10.1007/s13385-021-00279-w ------ The author would like to express his gratitude to the editor and to two anonymous referees for his or her careful review and insightful comments, that helped strengthen the quality of the paper. We thank also the suggestions and remarks from participants at the CAPSI 2020 Conference, Porto. The author was supported by Portuguese national science funds through FCT under the project UIDB/04152/2020-Centro de Investigação em Gestão de Informação (MagIC).
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spelling Pricing participating longevity-linked life annuitiesa Bayesian Model Ensemble approachBayesian Model EnsembleLongevity optionsLongevity-linked life annuitiesPensionsStochastic mortality modelsStatistics and ProbabilityEconomics and EconometricsStatistics, Probability and UncertaintySDG 1 - No PovertySDG 8 - Decent Work and Economic GrowthSDG 10 - Reduced InequalitiesBravo, J. M. (2022). Pricing participating longevity-linked life annuities: a Bayesian Model Ensemble approach. European Actuarial Journal, 12(1), 125-159. https://doi.org/10.1007/s13385-021-00279-w ------ The author would like to express his gratitude to the editor and to two anonymous referees for his or her careful review and insightful comments, that helped strengthen the quality of the paper. We thank also the suggestions and remarks from participants at the CAPSI 2020 Conference, Porto. The author was supported by Portuguese national science funds through FCT under the project UIDB/04152/2020-Centro de Investigação em Gestão de Informação (MagIC).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.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNBravo, Jorge Miguel2023-03-12T01:32:31Z2022-06-012022-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article35application/pdfhttp://hdl.handle.net/10362/118506eng2190-9733PURE: 31568999https://doi.org/10.1007/s13385-021-00279-winfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:01:23Zoai:run.unl.pt:10362/118506Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:43:55.015829Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Pricing participating longevity-linked life annuities
a Bayesian Model Ensemble approach
title Pricing participating longevity-linked life annuities
spellingShingle Pricing participating longevity-linked life annuities
Bravo, Jorge Miguel
Bayesian Model Ensemble
Longevity options
Longevity-linked life annuities
Pensions
Stochastic mortality models
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 1 - No Poverty
SDG 8 - Decent Work and Economic Growth
SDG 10 - Reduced Inequalities
title_short Pricing participating longevity-linked life annuities
title_full Pricing participating longevity-linked life annuities
title_fullStr Pricing participating longevity-linked life annuities
title_full_unstemmed Pricing participating longevity-linked life annuities
title_sort Pricing participating longevity-linked life annuities
author Bravo, Jorge Miguel
author_facet Bravo, Jorge Miguel
author_role author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Bravo, Jorge Miguel
dc.subject.por.fl_str_mv Bayesian Model Ensemble
Longevity options
Longevity-linked life annuities
Pensions
Stochastic mortality models
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 1 - No Poverty
SDG 8 - Decent Work and Economic Growth
SDG 10 - Reduced Inequalities
topic Bayesian Model Ensemble
Longevity options
Longevity-linked life annuities
Pensions
Stochastic mortality models
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 1 - No Poverty
SDG 8 - Decent Work and Economic Growth
SDG 10 - Reduced Inequalities
description Bravo, J. M. (2022). Pricing participating longevity-linked life annuities: a Bayesian Model Ensemble approach. European Actuarial Journal, 12(1), 125-159. https://doi.org/10.1007/s13385-021-00279-w ------ The author would like to express his gratitude to the editor and to two anonymous referees for his or her careful review and insightful comments, that helped strengthen the quality of the paper. We thank also the suggestions and remarks from participants at the CAPSI 2020 Conference, Porto. The author was supported by Portuguese national science funds through FCT under the project UIDB/04152/2020-Centro de Investigação em Gestão de Informação (MagIC).
publishDate 2022
dc.date.none.fl_str_mv 2022-06-01
2022-06-01T00:00:00Z
2023-03-12T01:32:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/118506
url http://hdl.handle.net/10362/118506
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2190-9733
PURE: 31568999
https://doi.org/10.1007/s13385-021-00279-w
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 35
application/pdf
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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