广西师范大学学报（自然科学版）Issue(2)：76-81,6.DOI:10.16088/j.issn.1001-6600.2015.02.012
基于极值理论的VaR和ES度量--以中兴通讯数据为例
Computing VaR and ES Based on the Extreme Value Theory:A Case Study of ZTE Data
摘要
Abstract
Value at Risk (VaR)is an important measurement tool for market risk.The Block Maxima Model (BMM)and the Peak Over Threshold (POT)model are employed to compute the VaR and Expected Shortfall (ES)for ZTE return data with heavy tails respectively.A discrepancy measure is proposed to select the threshold for the POT model.The data analysis shows that applying the extreme value theory in risk measurement can fully capture information from the tail of data and obtain reasonable VaR and ES to satisfy actual needs,and the results from the POT model are more stable than the ones from BMM.关键词
极值理论/风险价值/预期损失/BMM模型/POT模型Key words
extreme value theory/value at risk/expected shortfall/block maxima model/peak over threshold model分类
管理科学引用本文复制引用
丁新月,徐美萍..基于极值理论的VaR和ES度量--以中兴通讯数据为例[J].广西师范大学学报（自然科学版）,2015,(2):76-81,6.基金项目
国家自然科学基金资助项目(61304155) （61304155）
北京工商大学研究生部促进人才培养综合改革项目(19005428069) （19005428069）
