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Decisions in Economics and Finance

Erschienen in:

23.04.2019

Lévy CARMA models for shocks in mortality

verfasst von: Asmerilda Hitaj, Lorenzo Mercuri, Edit Rroji

Erschienen in: Decisions in Economics and Finance | Ausgabe 1/2019

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Abstract

Recent literature on mortality modeling suggests to include in the dynamics of mortality rates the effects of time, age, the interaction of these two and a term for possible shocks. In this paper we investigate models that use Legendre polynomials for the inclusion of age and cohort effects. In order to capture the dynamics of the shock term it is suggested to consider continuous autoregressive moving average (CARMA) models due to their flexibility in reproducing different autoregressive profiles of the shock term. In order to validate the proposed model, different life tables are considered. In particular the male life tables for New Zealand, Taiwan and Japan are used for the presentation of in-sample fitting. Empirical analysis suggests that the inclusion of more flexible models such as higher-order CARMA(p,q) models leads to better in-sample fitting.

Vorheriger Artikel Coherent modeling of mortality patterns for age-specific subgroups

Nächster Artikel Behavioral premium principles

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As observed in Loregian et al. (2012), in literature, several parametrizations for the Variance Gamma are available. In this paper, we use the parametrization considered by Madan and Seneta (1990), but we recall that it is always possible to switch from a parametrization to another through a proper parameter transformation.

The data on Human Mortality Database (2014) are collected yearly.

This is the same dataset used in Ahmadi and Gaillardetz (2015).

This is the null hypothesis.

This is the alternative hypothesis.

CARMA-BM(2,1) and CARMA-BM(2,0) are two nested models and therefore the LR-test is used.

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Titel: Lévy CARMA models for shocks in mortality
verfasst von: Asmerilda Hitaj
Lorenzo Mercuri
Edit Rroji
Publikationsdatum: 23.04.2019
Verlag: Springer International Publishing
Erschienen in: Decisions in Economics and Finance / Ausgabe 1/2019
Print ISSN: 1593-8883
Elektronische ISSN: 1129-6569
DOI: https://doi.org/10.1007/s10203-019-00248-9

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