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Title: A Quantitative Comparison of the Lee-Carter Model under Different Types of Non-Gaussian Innovations
Authors: 王昭文;黃泓智;劉議謙
Wang, Chou-Wen;Huang, Hong-Chih;Liu, I-Chien
Contributors: 風管系
Keywords: stochastic mortality model;non-Gaussian distributions;mortality jumps
Date: 2011.01
Issue Date: 2014-03-20 17:49:00 (UTC+8)
Abstract: 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—Student’s t-distribution and its skew extension (i.e., generalised hyperbolic skew Student’s 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, Cramér–von-Mises test) and out-of-sample projection errors indicate a preference for modelling the Lee-Carter model with non-Gaussian innovations.
Relation: The Geneva Papers on Risk and Insurance - Issues and Practice, 36(4), 675-696
Data Type: article
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Appears in Collections:[風險管理與保險學系 ] 期刊論文

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