Empirical Research On VaR Model On Chinese Stock Market Based On GJR-GARCH, FHS, Copula & EVT

In this paper,we study VaR model and its over-arching theories including FHS technology, GARCH model,Copula theory,Extreme Value Theory,etc,which are widely applied in describing,fitting and forecasting the financial time series as an effective and efficient approach to the evaluation and measure of the risk pertaining to the financial assets.This paper approximately consists of three empirical researches and simulations as follows: In the first place,we apply the classical VaR model,namely the Historical Simulation,to the measure of the Chinese security market risk.We utilize the parameter VaR method to carry on an empirical research to the security market of China,and calculate Value-at-Risk(VaR) of the Shanghai Composite Index,so as to examine the valid degree of this method in risk management of Chinese listed companies.The results show that from the contrast of actual value and lower limit of predicted VaR value,actual index value for 11 days breaks below the prediction lower limit.In the second place,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 distributed 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 in the first s ction.In the third place,we construct GJR-GARCH models to extract the residuals of logarithmic returns of Chinese stock indices,and estimate the distribution function of the residuals utilizing Gaussian kernel method and Extreme Value Theory.The kernel cumulative distribution function estimates are well suited for the interior of the distribution where most of the residuals are found and the POT method of Extreme Value Theory fits the extreme residuals in upper and lower tails well.Results show that during the holding period(one day) the greatest loss of this portfolio is 12.6225%and the greatest return rate is 8.9172%.The VaR values are -1.6377,-2.2782%and -4.2981%under the confidence level of 90%,95%and 99%respectively,namely we have 90% possibility that the loss is less than 1.6377%,have 95%possibility that the loss is less than 2.2782%and have 99%possibility that the loss is less than 4.2981%.