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題名 A Quantitative Comparison of the Lee-Carter Model under Different Types of Non-Gaussian Innovations
作者 王昭文;黃泓智;劉議謙
Wang, Chou-Wen ; Huang, Hong-Chih ; Liu, I-Chien
貢獻者 風管系
關鍵詞 stochastic mortality model; non-Gaussian distributions; mortality jumps
日期 2011.01
上傳時間 20-Mar-2014 17:49:00 (UTC+8)
摘要 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.
關聯 The Geneva Papers on Risk and Insurance - Issues and Practice, 36(4), 675-696
資料類型 article
DOI http://dx.doi.org/10.1057/gpp.2011.20
dc.contributor 風管系en_US
dc.creator (作者) 王昭文;黃泓智;劉議謙zh_TW
dc.creator (作者) Wang, Chou-Wen ; Huang, Hong-Chih ; Liu, I-Chienen_US
dc.date (日期) 2011.01en_US
dc.date.accessioned 20-Mar-2014 17:49:00 (UTC+8)-
dc.date.available 20-Mar-2014 17:49:00 (UTC+8)-
dc.date.issued (上傳時間) 20-Mar-2014 17:49:00 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/64775-
dc.description.abstract (摘要) 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.en_US
dc.format.extent 311269 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) The Geneva Papers on Risk and Insurance - Issues and Practice, 36(4), 675-696en_US
dc.subject (關鍵詞) stochastic mortality model; non-Gaussian distributions; mortality jumpsen_US
dc.title (題名) A Quantitative Comparison of the Lee-Carter Model under Different Types of Non-Gaussian Innovationsen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1057/gpp.2011.20en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1057/gpp.2011.20en_US