Models for stochastic mortality

Jan Iwanik

Applicationes Mathematicae (2007)

  • Volume: 34, Issue: 1, page 53-73
  • ISSN: 1233-7234

Abstract

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This paper is an attempt to present and analyse stochastic mortality models. We propose a couple of continuous-time stochastic models that are natural generalizations of the Gompertz law in the sense that they reduce to the Gompertz function when the volatility parameter is zero. We provide a statistical analysis of the available demographic data to show that the models fit historical data well. Finally, we give some practical examples for the multidimensional models.

How to cite

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Jan Iwanik. "Models for stochastic mortality." Applicationes Mathematicae 34.1 (2007): 53-73. <http://eudml.org/doc/278918>.

@article{JanIwanik2007,
abstract = {This paper is an attempt to present and analyse stochastic mortality models. We propose a couple of continuous-time stochastic models that are natural generalizations of the Gompertz law in the sense that they reduce to the Gompertz function when the volatility parameter is zero. We provide a statistical analysis of the available demographic data to show that the models fit historical data well. Finally, we give some practical examples for the multidimensional models.},
author = {Jan Iwanik},
journal = {Applicationes Mathematicae},
keywords = {stochastic mortality; systematic mortality risk; mortality options},
language = {eng},
number = {1},
pages = {53-73},
title = {Models for stochastic mortality},
url = {http://eudml.org/doc/278918},
volume = {34},
year = {2007},
}

TY - JOUR
AU - Jan Iwanik
TI - Models for stochastic mortality
JO - Applicationes Mathematicae
PY - 2007
VL - 34
IS - 1
SP - 53
EP - 73
AB - This paper is an attempt to present and analyse stochastic mortality models. We propose a couple of continuous-time stochastic models that are natural generalizations of the Gompertz law in the sense that they reduce to the Gompertz function when the volatility parameter is zero. We provide a statistical analysis of the available demographic data to show that the models fit historical data well. Finally, we give some practical examples for the multidimensional models.
LA - eng
KW - stochastic mortality; systematic mortality risk; mortality options
UR - http://eudml.org/doc/278918
ER -

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