Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/122030
Título: Pricing Survivor Bonds with Affine-Jump Diffusion Stochastic Mortality Models
Autor: Bravo, Jorge Miguel
Palavras-chave: Survivor bonds
Stochastic mortality models
Affine-jump diffusion
Longevity risk
Longevity-linked securities
Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software
SDG 3 - Good Health and Well-being
Data: 27-Jul-2021
Editora: ACM - Association for Computing Machinery
Resumo: Capital-market-based solutions are an interesting alternative to reinsurance-based options for managing systemic longevity risk in pension funds, insurance companies and annuity providers. The pricing of longevity-linked securities depends both on the stochastic process for the underlying risk factors (age-specific mortality rates, interest rate) and on investor's risk attitude. This paper proposes a pricing approach for survivor bonds using affine-jump diffusion stochastic mortality models. The model structure uses a non-mean reverting square-root jump diffusion Feller process combined with a Poisson process with double asymmetric exponentially distributed jumps to account for both negative and positive jumps. The model offers analytical tractability, fits well data and allows for closed-form expressions for the survival probability. Illustrative empirical results on the pricing of survivor bonds are provided using U. S. mortality data for representative cohorts. The results suggest the cost of hedging longevity risk by issuing survivor bonds would be acceptable for the issuer.
Descrição: Bravo, J. M. (2021). Pricing Survivor Bonds with Affine-Jump Diffusion Stochastic Mortality Models. In 2021 The 5th International Conference on E-Commerce, E-Business and E-Government ICEEG '21, April 28-30, 2021, Rome, Italy. Association for Computing Machinery (ACM). https://doi.org/10.1145/3466029.3466037 ---------------------------------------------------------------- Funding Information: The author acknowledges financial support by Portuguese national funds through FCT under the project UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC). Publisher Copyright: © 2021 Association for Computing Machinery. All rights reserved.
Peer review: yes
URI: http://hdl.handle.net/10362/122030
DOI: https://doi.org/10.1145/3466029.3466037
ISBN: 978-1-4503-8949-5
Aparece nas colecções:NIMS: MagIC - Documentos de conferências internacionais

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