A Value-at-Risk Analysis With Long Memory Of Volatility:Evidence From The Chinese Stock Market

摘要：

This paper investigate Value at Risk (VaR) measurement based on the long memory properties for closing prices of SSEC and SZEC in Chinese stock market. The FIGARCH(1, d, 1) and HYGARCH (1, d, 1) models with normal, student t and skew student t distribution of innovations are used to calculate dynamic VaR for long and short trading positions, and apply Kupiecs LR testing to test the accuracy of insample VaR measuring and out-of-sample VaR forecast ability of these models introduced in this paper. Our empirical results show that there exists significant long memory of volatility in Chinese stock markets; the skew student t distribution is the best to model the innovation of return, but normal is the worst to capture distribution of financial series. The FIGARCHd , d, 1) and HYGARCH(1, d, 1) models with skew student t distribution measure accurately dynamic VaR for SSEC and SZEC of Chinese stock market, and also exhibits outperform forecast ability of out-of-sample VaR.

关键词： long memory skewed and fat-tailed distribution value at risk HYGARCH LR testing

作者: CHUN Weide

作者单位: Business School. Chengdu University of Technology, Chengdu, P. R. China, 610059

会议类型: 国际会议

会议名称: 2010 International Conference on Management(2010管理国际大会)

会议地点: 上海

会议语种:英文

页码: 211-219

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）