东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2007, Vol. 28 ›› Issue (1): 141-144.DOI: -

• 论著 • 上一篇    下一篇

基于EGARCH-VaR的半参数法及实证研究

金秀;许宏宇;   

  1. 东北大学工商管理学院;东北大学工商管理学院 辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-27 修回日期:2013-06-27 出版日期:2007-01-15 发布日期:2013-06-24
  • 通讯作者: Jin, X.
  • 作者简介:-
  • 基金资助:
    辽宁省哲学社会科学规划基金资助项目(L05CJY035)

Semi-parameter approach based on EGARCH-VaR model and empirical research

Jin, Xiu (1); Xu, Hong-Yu (1)   

  1. (1) School of Business Administration, Northeastern University, Shenyang 110004, China
  • Received:2013-06-27 Revised:2013-06-27 Online:2007-01-15 Published:2013-06-24
  • Contact: Jin, X.
  • About author:-
  • Supported by:
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摘要： 在综合考虑了金融收益数据分布的尖峰厚尾特征及其波动集群性,尤其是其波动的“杠杆效应”对VaR估计的影响以及各种假定收益率分布在计算风险价值时存在不足的基础上,提出了基于EGARCH-VaR的半参数方法,并且与正态分布和t分布假设下的GARCH模型的VaR计量方法进行比较,通过实证分析,并利用后验测试,表明基于EGARCH-VaR的半参数方法对风险价值的测度优于正态分布和t分布假设下GARCH模型的VaR计量方法.

关键词: EGARCH模型, VaR, 半参数法, 后验测试

Abstract: In view of the peaked and fat-tailed characteristics of financial return data distribution and its effect of clustering fluctuation and especially the 'leverage effect' of fluctuation on VaR (value at risk) estimates and some efficiencies when estimating VaR with various assumptions of return data distribution, a semi-parameter approach based on EGARCH-VaR model is developed. This model is then compared with the approach based on to measuring VaR on the basis of GARCH model which is assumed to be normal/t distribution. An empirical analysis in combination with posterior testing is done on Chinese stock market risk, which shows that during VaR measuring the semi-parameter approach is superior to the approach based on GARCH model which is assumed normal/t distribution.

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