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政大機構典藏 > 商學院 > 風險管理與保險學系 > 期刊論文 > Item 140.119/61756

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/61756

Title:	Mortality Modeling with Non-Gaussian Innovations and Applications to the Valuation of Longevity Swaps
Authors:	黃泓智 Wang, Chou-Wen;Huang, Hong-Chih;Liu,I-Chien
Contributors:	風管系
Date:	2013-03
Issue Date:	2013-11-21 14:56:13 (UTC+8)
Abstract:	This article provides an iterative fitting algorithm to generate maximum likelihood estimates under the Cox regression model and employs non-Gaussian distributions—the jump diffusion (JD), variance gamma (VG), and normal inverse Gaussian (NIG) distributions—to model the error terms of the Renshaw and Haberman () (RH) model. In terms of mean absolute percentage error, the RH model with non-Gaussian innovations provides better mortality projections, using 1900–2009 mortality data from England and Wales, France, and Italy. Finally, the lower hedge costs of longevity swaps according to the RH model with non-Gaussian innovations are not only based on the lower swap curves implied by the best prediction model, but also in terms of the fatter tails of the unexpected losses it generates.
Relation:	Journal of Risk and Insurance,80(3),775-797
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1111/j.1539-6975.2013.12002.x
DOI:	10.1111/j.1539-6975.2013.12002.x
Appears in Collections:	[風險管理與保險學系] 期刊論文

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