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 Monte Carlo simulations we obtain a rough estimate of the policies’ value 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, and a regression method based on the class of generalized beta of the second kind distributions. Extensive numerical experiments are provided to assess the performance of the proposed models.

Modelling the Future Value Distribution of a Life Insurance Portfolio

Fabio Viviano;
2021-01-01

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 Monte Carlo simulations we obtain a rough estimate of the policies’ value 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, and a regression method based on the class of generalized beta of the second kind distributions. Extensive numerical experiments are provided to assess the performance of the proposed models.
2021
978-88-5511-258-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1213100
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