Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/258261 
Year of Publication: 
2021
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 9 [Issue:] 10 [Article No.:] 177 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-17
Publisher: 
MDPI, Basel
Abstract: 
This paper addresses the problem of approximating the future value distribution of a large and heterogeneous life insurance portfolio which would play a relevant role, for instance, for solvency capital requirement valuations. Based on a metamodel, we first select a subset of representative policies in the portfolio. Then, by using Monte Carlo simulations, we obtain a rough estimate of the policies' values at the chosen future date and finally we approximate the distribution of a single policy and of the entire portfolio by means of two different approaches, the ordinary least-squares method and a regression method based on the class of generalized beta distribution of the second kind. Extensive numerical experiments are provided to assess the performance of the proposed models.
Subjects: 
GB2
LSMC
metamodel
regression models
Solvency II
JEL: 
G22
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
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