Document type
ArticleVersion
Published versionPublication date
Publication license
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/183149
Nonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk
Journal Title
Director/Tutor
Journal ISSN
Volume Title
Related resource
Abstract
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.
Subject (English)
Citation
Citation
BOLANCÉ LOSILLA, Catalina and GUILLÉN, Montserrat. Nonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk. Risks . 2021. Vol. 9(4), num. 77, pags. 1-23. ISSN 2227-9091. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/183149