Centro de Documentacion de Fundación MAPFRE - A Quantitative comparison of the Lee-Carter model under different types of non-Gaussian Innovations

Notas: Sumario: In the classical Lee-Carter model, the mortality indices that are assumed to be a random walk model with drift are normally distributed. However, for the long-term mortality data, the error terms of the Lee-Carter model and the mortality indices have tails thicker than those of a normal distribution and appear to be skewed. This study therefore adopts five non-Gaussian distributions Students t-distribution and its skew extension (i.e., generalised hyperbolic skew Students t-distribution), one finite-activity Lévy model (jump diffusion distribution), and two infinite-activity or pure jump models (variance gamma and normal inverse Gaussian) to model the error terms of the Lee-Carter model. With mortality data from six countries over the period 1900-2007, both in-sample model selection criteria (e.g., Bayesian information criterion, Kolmogorov Smirnov test, Anderson Darling test, Cramérvon-Mises test) and out-of-sample projection errors indicate a preference for modelling the Lee-Carter model with non-Gaussian innovationsRegistros relacionados: En: Geneva papers on risk and insurance : issues and practice. - Geneva : The Geneva Association, 1976- = ISSN 1018-5895. - 03/10/2011 Tomo 36 Número 4 - 2011 , p. 675-696Materia / lugar / evento: Matemática del seguro Modelos actuariales Mortalidad Longevidad Seguro de vida Otros autores: Huang, Hong-Chih
Liu, I - Chien
Outras classificações: 6

Direitos: In Copyright (InC)

‌ Ver detalhe do número