您的位置:首页  > 论文页面

基于滞后虚拟变量分位点回归模型的条件VaR估计

发表时间:2012-01-15  浏览量:1684  下载量:757
全部作者: 裴培,贺仁癸,严定琪
作者单位: 兰州大学数学与统计学院
摘 要: 建立含有滞后虚拟变量的分位点回归模型,并应用此模型分析流动性风险指标条件下的条件在险价值(value at risk, VaR)。经过实证分析发现:含有二阶滞后虚拟变量的分位点回归模型模拟数据得到的结果比线性分位点回归模型和基于流动性风险指标的虚拟变量分位点回归模型模拟得到的结果更好。而且,由条件VaR的事后检验可知:含有二阶滞后虚拟变量的分位点回归模型能更好地估计条件VaR.
关 键 词: 时间序列分析;含滞后虚拟变量的分位点回归模型;含虚拟变量的分位点回归模型;线性分位点回归模型;条件在险价值;事后检验
Title: Estimation of conditional VaR based on the lag and dull variable quantile regression model
Author: PEI Pei, HE Rengui, YAN Dingqi
Organization: School of Mathematics and Statistics, Lanzhou University
Abstract: In this paper, the lag and dull variable quantile regression model is presented to estimate the conditional value at risk (VaR), which is conditioned on the liquidity risk measure. By the empirical analysis, it is found that the lag 2 and dull variable quantile regression model can better describe real data than the linear quantile regression model and the dull variable quantile regression model based on the liquidity risk measure. And by the back testing of the conditional value at risk, the conditional value at risk can be better simulated by the lag 2 and dull variable quantile regression model.
Key words: time series analysis; lag and dull variable quantile regression model; dull variable quantile regression model; linear quantile regression model; conditional value at risk; back-test methods
发表期数: 2012年1月第1期
引用格式: 裴培,贺仁癸,严定琪. 基于滞后虚拟变量分位点回归模型的条件VaR估计[J]. 中国科技论文在线精品论文,2012,5(1):6-11.
 
0 评论数 0
暂无评论
友情链接