Faculty of Actuarial Science & Insurance Seminar with David Atance - Universidad de Alcala
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In this paper, we develop a model to construct dynamic life tables based on the idea that the behavior of whole life table can be explained by a reduced number of fac-tors. In this case these factors are identified with some mortality rates at specific ages. These key mortality rates and model parameters estimates are obtained applying a maximum likelihood criteria under the hypothesis of a binomial distribution of the number of deaths. In this paper, we develop the single factor version of the model which is implemented to the male and female populations of France and Spain. The model is compared with a set of alternative well-known life tables models. To test the forecasting ability of the model we apply a battery of tests using out of sample data. Despite its simplicity, the outcomes indicate that this model it is not outperformed by other more complex mortality models. Another important advantage of this model is that can it be easily implemented to address some longevity risk linked problems in the context of Solvency II.
Where
Bayes Business School, 106 Bunhill Row
Room 2005
106 Bunhill Row, London EC1Y 8TZ, UK