Non-life loss reserving models based on heavy-tailed distributions

doi:10.12011/1000-6788-2018-0973-13

LZUFE-KMS

	Non-life loss reserving models based on heavy-tailed distributions
	Huang, Yifan 1; Meng, Shengwang 1,2
	2020
发表期刊	Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
卷号	40 期号:1 页码:42-54
摘要	The estimation of outstanding claims reserve is the core work of solvency management in Property & Casualty insurance companies. Common methods for claims reserving are generalized linear models (GLMs). However, traditional distributional assumptions of GLMs may not match actual incremental losses when the heavy-tailed feature exists, and meanwhile, dependencies among multiple run-off triangles also require a model to combine reserve assessments of individual lines of business (LoBs). This paper replaced traditional assumptions of gamma, lognormal and GB2 distributions with three new heavytailed distributions (i.e. exponentiated Fréchet distribution, generalized log-Moyal distribution and full tails Gamma distribution), investigated their application effects in outstanding claims reserving and finally applied Copula regressions to describe dependent structures among different LoBs. The predictive distribution and risk measurements of total reserves can be obtained by parametric bootstrap and Monte Carlo simulations. The empirical results based on an actual dataset show that, heavy-tailed distributions are of high values in improving the prediction of outstanding claims reserves, and the adjustment of reserves' dependencies makes the prediction more rational. © 2020, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
关键词	Insurance Claims reserving Copula Gamma distribution Generalized linear model Heavy tailed distribution Insurance companies Parametric bootstrap Predictive distributions
DOI	10.12011/1000-6788-2018-0973-13
收录类别	EI ; SCOPUS ; 北大核心 ; CSCD ; CSSCI
ISSN	10006788
语种	中文
出版者	Systems Engineering Society of China
EI入藏号	20201008259405
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/509
专题	兰州财经大学
作者单位	1.Center for Applied Statistics, Renmin University of China, Beijing; 2.100872, China; 3.School of Statistics, Lanzhou University of Finance and Economics, Lanzhou; 4.730020, China
推荐引用方式 GB/T 7714	Huang, Yifan,Meng, Shengwang. Non-life loss reserving models based on heavy-tailed distributions[J]. Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice,2020,40(1):42-54.
APA	Huang, Yifan,&Meng, Shengwang.(2020).Non-life loss reserving models based on heavy-tailed distributions.Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice,40(1),42-54.
MLA	Huang, Yifan,et al."Non-life loss reserving models based on heavy-tailed distributions".Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice 40.1(2020):42-54.