Abstract
ABSTRACTLife tables used in life insurance are often calibrated to show the survival function of the age of death distribution at exact integer ages. Actuaries usually make fractional age assumptions (FAAs) when having to value payments that are not restricted to integer ages. Traditional FAAs have the advantage of simplicity but cannot guarantee to capture precisely the real trends of the survival functions and sometimes even result in a non intuitive overall shape of the force of mortality. In fact, an FAA is an interpolation between integer age values which are accepted as given. In this article, we introduce Kriging model, which is widely used as a metamodel for expensive simulations, to fit the survival function at integer ages, and furthermore use the precisely constructed survival function to build the force of mortality and the life expectancy. The experimental results obtained from a simulated life table (Makehamized life table) and two “real” life tables (the Chinese and US life tables) show that these actuarial quantities (survival function, force of mortality, and life expectancy) presented by Kriging model are much more accurate than those presented by commonly-used FAAs: the uniform distribution of death (UDD) assumption, the constant force assumption, and the Balducci assumption.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.