Empirical likelihood-based evaluations of Value at Risk models  

作　　者：WEI ZhengHong WEN SongQiao ZHU LiXing 

机构地区：[1]College of Mathematics and Computational Science,Shenzhen University,Shenzhen 518060,China [2]Department of Mathematics,Hongkong Baptist University,Hong Kong

出　　处：《Science China Mathematics》2009年第9期1995-2006,共12页中国科学：数学（英文版）

基　　金：supported by Guangdong Natural Science Foundation (Grant No.2008276);a grant from the Research Grants Council of Hong Kong,China

摘　　要：Value at Risk (VaR) is a basic and very useful tool in measuring market risks. Numerous VaR models have been proposed in literature. Therefore, it is of great interest to evaluate the efficiency of these models, and to select the most appropriate one. In this paper, we shall propose to use the empirical likelihood approach to evaluate these models. Simulation results and real life examples show that the empirical likelihood method is more powerful and more robust than some of the asymptotic method available in literature.Value at Risk (VaR) is a basic and very useful tool in measuring market risks. Numerous VaR models have been proposed in literature. Therefore, it is of great interest to evaluate the efficiency of these models, and to select the most appropriate one. In this paper, we shall propose to use the empirical likelihood approach to evaluate these models. Simulation results and real life examples show that the empirical likelihood method is more powerful and more robust than some of the asymptotic method available in literature.

关 键 词：Value at Risk VOLATILITY empirical likelihood specification test non-nested test 62G10 62P20 91B30 

分 类 号：O211.67[理学—概率论与数理统计]