END序列样本VaR核估计的Bahadur表示  

Bahadur Representation of VaR Kernel Estimation for END Sequence Samples

作　　者：王巍 朱勇 王文琴 WANG Wei;ZHU Yong;WANG Wenqin(College of Big Data and Artificial Intelligence,Chizhou University,Chizhou 247000,China)

机构地区：[1]池州学院大数据与人工智能学院,安徽池州247000

出　　处：《新乡学院学报》2022年第3期1-4,共4页Journal of Xinxiang University

基　　金：安徽省自然科学基金项目(2108085QA15);安徽高校自然科学研究重点项目(KJ2018A0579);安徽高校人文社会科学研究项目(SK2021A0739)。

摘　　要：利用END序列的性质及其指数不等式研究了风险测度VaR核估计的性质,证明了VaR核估计的强相合性并得到其收敛速率,同时也给出了VaR核估计的Bahadur表示,将VaR核估计推广到了END样本。The properties of VaR kernel estimation of risk measure are studied by the properties of END sequence and its exponential inequality.The strong consistency of VaR kernel estimation is proved and its convergence rate is obtained.At the same time,the Bahadur representation of VaR kernel estimation is given,and the VaR kernel estimation is extended to END samples.

关 键 词：END样本 VaR核估计 BAHADUR表示 

分 类 号：O211.4[理学—概率论与数理统计]