一类带有宽负相依索赔额的新风险模型损失过程的精细大偏差

删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

本站小编 Free考研考试/2021-12-27

一类带有宽负相依索赔额的新风险模型损失过程的精细大偏差唐风琴¹, 白建明², 尹晓玲²1 淮北师范大学数学科学学院, 淮北 235000;
2 兰州大学管理学院, 兰州 730000 Precise Large Deviations for Loss Process of a New Risk Model with Extended Negatively Dependent Claim Sizes TANG Fengqin¹, BAI Jianming², YIN Xiaoling²1 School of Mathematics Sciences, Huaibei Normal University, Huaibei 235000;
2 School of Management, Lanzhou University, Lanzhou 730000

摘要
图/表
参考文献
相关文章(6)
点击分布统计
下载分布统计
-->

全文: PDF(341 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要本文研究一类基于保单进入过程的风险模型，客户在其保期内可索赔多次.假设每个顾客的索赔额是宽负相依的且服从重尾分布，不同顾客之间的索赔额是相互独立的.本文得到了损失过程的大偏差.

服务

加入引用管理器

E-mail Alert

RSS

收稿日期: 2017-03-14

PACS:	O211.65
	O211.66

基金资助:国家自然科学基金（71171103）以及安徽省高校自然科学研究重点项目（KJ2017A377）资助.

引用本文:

唐风琴, 白建明, 尹晓玲. 一类带有宽负相依索赔额的新风险模型损失过程的精细大偏差[J]. 应用数学学报, 2019, 42(1): 43-54. TANG Fengqin, BAI Jianming, YIN Xiaoling. Precise Large Deviations for Loss Process of a New Risk Model with Extended Negatively Dependent Claim Sizes. Acta Mathematicae Applicatae Sinica, 2019, 42(1): 43-54.

链接本文:

http://123.57.41.99/jweb_yysxxb/CN/或 http://123.57.41.99/jweb_yysxxb/CN/Y2019/V42/I1/43

[1]	Li Z H, Kong X B. A new risk model based on policy entrance process and its weak convergence properties. Appl. Stoch. Model. Bus., 2007, 3(23):235-246
[2]	Chen Y, Ng K W. The ruin probability of the renewal model with constant interest force and negatively dependent heavy-tailed claims. Insur. Math. Econ., 2007, 40(3):415-423
[3]	杨洋, 林金官, 高庆武. 时间相依更新风险模型中无限时绝对破产概率的渐近性. 中国科学:数学, 2013, 2(43):173-184(Yang Y, Lin J G, Gao Q W. Asymptotics for the infinite-time absolute ruin probabilities in timedependent renewal risk models. Sci. China. Math., 2013, 2(43):173-184)
[4]	Liu X J, Yu C J, Gao Q W. Precise large deviations of aggregate claim amount in a dependent renewal risk model. Commun. Stat-Theor. M., 2017, 5(46):2354-2363
[5]	Klüppelberg C, Mikosch T. Large deviations of heavy-tailed random sums with applications in insurance and finance. J. Appl. Probab., 1997, 34(2):293-308
[6]	Mikosch T, Nagaev A V. Large deviations heavy-tailed sums with applications in insurance. Extremes, 1998, 1(1):81-110
[7]	Tang Q. Insensitivity to negative dependence of the asymptotic behavior of precise large deviations. Electron. J. Probab., 2006, 11:107-120
[8]	Chen Y, Zhang W P. Large deviations for random sums of negatively dependent random variables with consistently varying tails. Stat. Probabil. Lett., 2007, 5(77):530-538
[9]	Chen Y Q, Yuen K C, Ng K W. Precise Large Deviations of Random Sums in Presence of Negative Dependence and Consistent Variation. Methodol. Comput. Appl., 2011, 13(4):821-833
[10]	Liu L. Precise large deviations for dependent random variables with heavy tails. Stat. Probabil. Lett., 2009, 79(9):1290-1298
[11]	Ng K, Tang Q, Yan J, Yang H. Precise large deviations for sums of random variables with consistently varying tails. J. Appl. Probab., 2004, 1(41):93-107
[12]	Tang Q. Insensitivity to negative dependence of asymptotic tail probabilities of sums and maxima of sums. Stoch. Anal. Appl., 2008, 3(26):435-450
[13]	Tang Q, Su Q, Jiang T, Zhang J. Large deviations for heavy-tailed random sums in compound renewal model. Stat. Probabil. Lett., 2001, 1(52):91-100
[14]	Tang F, Bai J. Precise large deviations for aggregate loss process in a multi-risk model. J. Koren. Math. Soc., 2015, 52(3):447-467
[15]	Wang D, Tang Q. Maxima of sums and random sums for negatively associated random variables with heavy tails. Stat. Probabil. Lett., 2004, 3(68):287-295
[16]	Kaas R, Tang Q. A large deviation result for aggregate claims with dependent claim occurrences. Insur. Math. Econom., 2005, 3(36):251-259

[1]	毕秀春, 张曙光, 李荣. 一类重灾风险模型的生存概率[J]. 应用数学学报(英文版), 2012, 35(5): 817-828.
[2]	肖鸿民, 李泽慧. 一类新风险过程的精细大偏差[J]. 应用数学学报(英文版), 2010, 33(5): 900-909.
[3]	肖鸿民, 李泽慧. 一类新风险过程的精细大偏差[J]. 应用数学学报(英文版), 2010, 33(1): 900-909.
[4]	张志祥. 大偏差结果的一个简单证明[J]. 应用数学学报(英文版), 2001, 17(3): 326-331.
[5]	张志祥. 大偏差结果的一个简单证明[J]. 应用数学学报(英文版), 2001, 17(3): 326-331.
[6]	席福宝. 退化扩散过程小扰动的平均越出时间估计[J]. 应用数学学报(英文版), 1997, 20(2): 0-0.

PDF全文下载地址:

http://123.57.41.99/jweb_yysxxb/CN/article/downloadArticleFile.do?attachType=PDF&id=14590