Application of the Markov Chains in the Prediction of the Mortality Rates in the Generalized Stochastic Milevsky–Promislov Model

Piotr S̀liwka ()
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Piotr S̀liwka: Cardinal Stefan Wyszyǹski University, Department of Mathematics and Natural Sciences

A chapter in Trends in Biomathematics: Mathematical Modeling for Health, Harvesting, and Population Dynamics, 2019, pp 191-208 from Springer

Abstract: Abstract The modeling and forecasting of the mortality rates plays an important role in the field of life insurance, as well as in the area of the public health. The advantage of using the continuous Gaussian process excitations to model mortality coefficients in relation to the commonly applied Lee–Carter model (Lee and Carter, J Am Stat Assoc 87:659, 1992) and usefulness with switches of the former models is shown in the article of S̀liwka and Socha (Scand Actuar J, 2018. www.doi.org/10.1080/03461238.2018.1431805 ). The aim of this work is to examine the possibility of using Markov chains (finite homogeneous Markov chain and Markov set-chains in the case when the homogeneity condition is not fulfilled) to predict the time switching points between mortality rates modeled on the basis of the generalized stochastic Milevsky–Promislov model. The obtained preliminary results confirm the usefulness of the proposed approach.

Keywords: Forecasting of mortality rates; Hybrid mortality models; Markov (set) chain; Markov switching models; Ito stochastic differential equations (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-23433-1_14

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DOI: 10.1007/978-3-030-23433-1_14

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