风险价值VaR的区间估计

doi:10.6040/j.issn.1671-9352.0.2016.033

山东大学学报（理学版） ›› 2017, Vol. 52 ›› Issue (2): 85-90.doi: 10.6040/j.issn.1671-9352.0.2016.033

风险价值VaR的区间估计

任鹏程,徐静,李新民^*

青岛大学数学与统计学院, 山东青岛 266071

收稿日期:2016-01-19 出版日期:2017-02-20 发布日期:2017-01-18
通讯作者: 李新民(1969— ),男,博士,教授,研究方向为数理统计及其应用.E-mail:xmli@qdu.edu.cn E-mail:renpengcheng12@qq.com
作者简介:任鹏程(1992— ),男,硕士研究生,研究方向为数理统计及其应用.E-mail:renpengcheng12@qq.com
基金资助:
国家自然科学基金资助项目(11501314);山东省自然科学基金资助项目(ZR2014AM019)

Interval estimation of VaR

REN Peng-cheng, XU Jing, LI Xin-min^*

School of Mathematics and Statistics, Qingdao University, Qingdao 266071, Shandong, China

Received:2016-01-19 Online:2017-02-20 Published:2017-01-18

摘要/Abstract

摘要： 风险价值(value at risk, VaR)是国际金融界广泛支持和认可的一种度量金融风险的工具。分别利用Bootstrap、MOVER(method of variance estimates recovery)和Fiducial方法给出正态总体下VaR的区间估计方法,并进行了模拟比较。模拟结果发现基于Fiducial思想的广义区间估计在覆盖率和区间等尾性上具有更稳健的性质。最后对上证180重点指数的对数收益率VaR进行了分析。

关键词: MOVER, Bootstrap法, 区间估计, 风险价值, 广义推断

Abstract: Value at risk(VaR)is a tool used for measuring financial risk, which is widely supported and recognized by international finance. To study the interval estimation method in normal population, we used three methods such as Bootstrap、MOVER(method of variance estimates recovery)and Fiducial, and numerically compare the performance of them. The simulation results show that generalized interval estimation based on Ficucial is more robust in coverage and balanced tail error. In the end, the VaR of logarithmic yield of SSE 180 was analyzed.

Key words: VaR, Bootstrap method, MOVER, generalized inference, interval estimation

中图分类号:

O212.1

任鹏程,徐静,李新民. 风险价值VaR的区间估计[J]. 山东大学学报（理学版）, 2017, 52(2): 85-90.

REN Peng-cheng, XU Jing, LI Xin-min. Interval estimation of VaR[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2017, 52(2): 85-90.

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风险价值VaR的区间估计

Interval estimation of VaR

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