A square-root factor-based multi-population extension of the mortality laws

Petar Jevtić; Luca Regis

doi:10.3390/math9192402

A square-root factor-based multi-population extension of the mortality laws

Petar Jevtić, Luca Regis

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.

Original language	English (US)
Article number	2402
Journal	Mathematics
Volume	9
Issue number	19
DOIs	https://doi.org/10.3390/math9192402
State	Published - Oct 1 2021
Externally published	Yes

Keywords

Continuous-time stochastic mortality
Mortality surface
Multi-population mortality
Quasi-linear Kalman filter estimation
Square-root processes

ASJC Scopus subject areas

Mathematics(all)

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10.3390/math9192402

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title = "A square-root factor-based multi-population extension of the mortality laws",

abstract = "In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.",

keywords = "Continuous-time stochastic mortality, Mortality surface, Multi-population mortality, Quasi-linear Kalman filter estimation, Square-root processes",

author = "Petar Jevti{\'c} and Luca Regis",

note = "Funding Information: This research was partially funded by the {"}Dipartimenti di Eccellenza 2018-2022{"} grant by the Italian Ministry of Education and Research. Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",

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AU - Jevtić, Petar

AU - Regis, Luca

N1 - Funding Information: This research was partially funded by the "Dipartimenti di Eccellenza 2018-2022" grant by the Italian Ministry of Education and Research. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/10/1

Y1 - 2021/10/1

N2 - In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.

AB - In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.

KW - Continuous-time stochastic mortality

KW - Mortality surface

KW - Multi-population mortality

KW - Quasi-linear Kalman filter estimation

KW - Square-root processes

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ER -

A square-root factor-based multi-population extension of the mortality laws

Abstract

Keywords

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