• 论文 •

### 基于尾部样本数据的尾部相关性分析

1. 山东科技大学数学与系统科学学院, 山东 青岛 266590
• 收稿日期:2014-04-11 修回日期:2014-09-18 出版日期:2014-12-20 发布日期:2014-12-20
• 作者简介:李述山(1966- ),男,博士,教授,研究方向为统计推断理论及应用、风险管理. E-mail:ss_li2002@aliyun.com
• 基金资助:
高等学校博士点专项科研基金资助项目(20123718110010)

### Tail dependence analysis based on tail sample data

LI Shu-shan

1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
• Received:2014-04-11 Revised:2014-09-18 Online:2014-12-20 Published:2014-12-20

Abstract: Tail dependence is the nature of the tail to the joint distribution of the two random variables. Be directed against tail dependence analysis, two concepts of order statistics for 2-dimension random vector were proposed and an idea was advanced to estimate the tail dependence coefficient by fitting Copula function using tail sample. Then the method of parameter estimation and fitting tests for the tail based on tail sample date and the corresponding estimate method for tail dependence coefficient were also discussed. A Monte Carlo simulation was given to illustrate the validity of the method given. Finally the tail dependence between the SHI and the SZI was analyzed.

• O212
 [1] JOE H. Multivariate models and dependence concepts[M]. London: Chapman and Hall, 1997. [2] NELSEN R B. An Introduction to copulas[M]. New York: Springer, 1999. [3] FREES E W, VALDEZ E A. Understanding relationships using copulas[J]. North American Actuarial Journal, 1998, 2 (1):1-25. [4] 张尧庭.连接函数(Copula) 技术与金融风险分析[J].统计研究,2002(4):48-51. ZHANG Yaoting. Analysis of technical and financial risk of the link function (Copula)[J].Statistical Research, 2002(4):48-51. [5] 韦艳华,张世英.金融市场非对称尾部相关性结构的研究[J].管理科学,2005(9):601-605. WEI Yanhua, ZHANG Shiying. Research on asymmetric tail dependence structure in financial markets[J]. Chinese Journal of Management, 2005(9):601-605. [6] 李悦,程希骏.上证指数和恒生指数的Copula尾部相关性分析[J].系统工程,2006(149):88-92. LI Yue, CHENG Xijun. Tail dependence analysis of SZI & HSI based on Copula method[J]. Systems Engineering, 2006(149):88-92. [7] REMILLARD B, GENEST C, BEAUDOIN D. Goodness-of-fit tests for copulas: a review and a power study[J]. Mathematics and Economics, 2007(10):46-52. [8] 李述山.金融时间序列间的条件相关性分析与Copula的选择原则[J].统计与决策,2010(4):23-25. LI Shushan. Analysis of correlation between financial time series and selection principle of Copula[J]. Statistics & Decision, 2010(4):23-25. [9] 李述山.阿基米德Copula函数的拟合检验[J].统计与决策,2012(12):77-78. LI Shushan. Goodness of fit of the archimedes Copula function[J]. Statistics & Decision, 2012(12):77-78. [10] BERG D, AAS K. Models for construction of multivariate dependence: a comparison study[J]. The European Journal of Finance, 2009(7-8):639-659.
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