Uncertainty Comparison Between Value-at-Risk and Expected Shortfall  

作　　者：Qing Liu Weimin Liu Liang Peng Gengsheng Qin 

机构地区：[1]School of Statistics,Jjiangxi University of Finance and Economics,Nanchang,Jiangxi 330013,China [2]Department of Mathematics and Statistics,Georgia State University,Atlanta,GA 30303,USA [3]Maurice R.Greenberg School of Risk Science,Georgia State University,Atlanta,GA 20303,USA

出　　处：《Communications in Mathematical Research》2024年第1期102-124,共23页数学研究通讯（英文版）

摘　　要：Value-at-Risk(VaR)and expected shortfall(ES)are two key risk measures in financial risk management.Comparing these two measures has been a hot debate,and most discussions focus on risk measure properties.This paper uses independent data and autoregressive models with normal or t-distribution to examine the effect of the heavy tail and dependence on comparing the nonparametric inference uncertainty of these two risk measures.Theoretical and numerical analyses suggest that VaR at 99%level is better than ES at 97.5%level for distributions with heavier tails.

关 键 词：Α-MIXING asymptotic variance expected shortfall VALUE-AT-RISK 

分 类 号：F83[经济管理—金融学] O17[理学—数学]