Nonparametric estimation of extreme quantiles with an application to longevity risk

Artikel

A new method to estimate longevity risk based on the kernel estimation of the extreme quantiles of truncated age-at-death distributions is proposed. Its theoretical properties are presented and a simulation study is reported. The flexible yet accurate estimation of extreme quantiles of age-at-death conditional on having survived a certain age is fundamental for evaluating the risk of lifetime insurance. Our proposal combines a parametric distributions with nonparametric sample information, leading to obtain an asymptotic unbiased estimator of extreme quantiles for alternative distributions with different right tail shape, i.e., heavy tail or exponential tail. A method for estimating the longevity risk of a continuous temporary annuity is also shown. We illustrate our proposal with an application to the official age-at-death statistics of the population in Spain.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Risks ; ISSN: 2227-9091 ; Volume: 9 ; Year: 2021 ; Issue: 4 ; Pages: 1-23 ; Basel: MDPI

Classification and Topics

• Classification: Wirtschaft
• Subject: extreme quantile ; extreme value distribution ; kernel estimation ; lifetime annuity

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bolancé, Catalina ; Guillén, Montserrat
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2021

Further information

• DOI: doi:10.3390/risks9040077
• Handle: http://hdl.handle.net/10419/258165
• Last update: 10.03.2025, 11:43 AM CET