Science Journal of Applied Mathematics and Statistics
Volume 3, Issue 3, June 2015, Pages: 70-74
Received: Mar. 30, 2015;
Accepted: Apr. 16, 2015;
Published: Apr. 27, 2015
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Hong Zhang, School of Information, Beijing Wuzi University, Beijing, China
Jian Guo, School of Information, Beijing Wuzi University, Beijing, China
Li Zhou, School of Information, Beijing Wuzi University, Beijing, China
In this paper, we establish GJR-GARCH models to extract the residuals of logarithmic returns of one kind of Chinese stock index--- Shanghai Composite Index and the series of independent and identically distribution standardized residuals is formed from the filtered model residuals and conditional volatilities from the return series with an GJR-GARCH model. The results show that from the contrast of actual value and lower limit of predicted VaR value, actual index value for 8 days breaks below the prediction lower limit. The fitting result of VaR method to the market risk of the Shanghai composite index is better than that of the Traditional Historical Simulation.
Study on Financial Market Risk Measurement Based on GJR-GARCH and FHS, Science Journal of Applied Mathematics and Statistics.
Vol. 3, No. 3,
2015, pp. 70-74.
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