Econometric Model Analysis On Dynamic VaR And CVaR Of China's Stock Market

In recent twenty years, Financial Market Risk becomes an attention focus with Global Financial Institutions and Supervising authorities. With it correspondence, risk measurement technology also obtained the development in the recent years. Among them, The value at risk (VaR) and the condition of value at risk (CVaR) are the most popular two risk measurement methods. Therefore, it is a hot topic of discussion to how to structure a suitable model to measure financial risk at current finance research area. when we calculate VaR and CVaR by using parameter method, distribution hypothesis and the select of models are somewhat subjectivity and sometimes depending on experience. This article analyzes the Shanghai and Shenzhen stock markets index from statistical characteristic obtaining, taking the APARCH as the foundation, I calculate its dynamic VaR and CVaR under many kinds of distribution supposition, The main contents and results are as follows:(1)At present, Stock market is still in the development initial period in Our country, chosing the appropriate distribution to portray the market returns ratio appears extremely important, this article embarked from Stock market's logarithm returns ratio data of Our country, the returns ratio of Shanghai and Shenzhen Stock Market are analyzed by means of laplace distribution simulation. All parameters are estimated by the maximum likely estimation and distribution simulation optimistic is measuredχ2test and Dn test. The results show that the laplace distribution is fitter for real return of Chinese stock market than normal distribution.(2) This paper studies the basic principles and methods of VaR and CVaR. We analysis GARCH family such as GARCH, APARCH, and compute VaR and CVaR about Index of Shanghai Stock Exchange based on normal distribution and Laplace distribution. we compare the results and draw some new conclusions(3) Since shenzhen B-share indices is characterized with skewness and abnormal fluctuations, the return series are simulated with an asymmetric laplace distribution. And distribution simulation optimistic is measured byχ2 test and Dn test. The results show that the asymmetric laplace distribution is fitter compared with the symmetric distributon of normal and Laplace. On this basis, the asymmetric laplace distribution is introduced into GARCH and APARCH mordel for empirical study on VaR and CVaR of shenzhen B-share indices. We have given the algorithm realization using matlab and eviews, and have obtained some significance findings.(4)In reality the financial field, various risks is interactional and proliferational. It is need to study a certain variables on a risk measure the impact. The VaR Under certain conditions (conditions VaR), which can be described the relationship between certain risks and variables. Therefore,this article Research the VaR under the liquidity risk conditions. Nonparametric method was used to establish the model of dynamic VaR and CVaR. Finally, an empirical analysis on two stock indexes Chinese and a satisfied result was obtained.