Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257855 
Year of Publication: 
2019
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 7 [Issue:] 1 [Article No.:] 17 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-22
Publisher: 
MDPI, Basel
Abstract: 
Phase-type (PH) distributions are defined as distributions of lifetimes of finite continuous-time Markov processes. Their traditional applications are in queueing, insurance risk, and reliability, but more recently, also in finance and, though to a lesser extent, to life and health insurance. The advantage is that PH distributions form a dense class and that problems having explicit solutions for exponential distributions typically become computationally tractable under PH assumptions. In the first part of this paper, fitting of PH distributions to human lifetimes is considered. The class of generalized Coxian distributions is given special attention. In part, some new software is developed. In the second part, pricing of life insurance products such as guaranteed minimum death benefit and high-water benefit is treated for the case where the lifetime distribution is approximated by a PH distribution and the underlying asset price process is described by a jump diffusion with PH jumps. The expressions are typically explicit in terms of matrix-exponentials involving two matrices closely related to the Wiener-Hopf factorization, for which recently, a Lévy process version has been developed for a PH horizon. The computational power of the method of the approach is illustrated via a number of numerical examples.
Subjects: 
generalized Coxian distribution
EM algorithm
guaranteed minimum death benefit
high-water benefit
jump diffusion
matrix-analytic methods
reserves
Wiener-Hopf factorization
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Appears in Collections:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.