Study On The Volatility Of China's Stock Market Based On Realized GARCH Model Under NIG Distribution

As the trend of economic globalization increases obviously,the volatility of stock markets are also inextricably linked.For developing China,economic globalization brings more opportunities and resources,which promotes China's unprecedented economic leap in a short time.On the other hand,the economic environment of China,even the world,is bocoming more complex and changeable.Morever,the risk is increasing.Therefore,only grasping the law of volatility of stock markets,especially the volatility in extreme times,can we predict and avoid risk effectively.The correct selection of both the financial models and the distribution of returns is of vital importance when estimating the volatility of stock market.Realized GARCH model combines GARCH model with realized volatility.Using realized measures to reflect volatility can overcome the drawbacks in the traditional fluctuation model.And because NIG distribution contains many advantages of generalized hyperbolic levy process,it is applicable to a variety of situations,especially the extreme times of stock market.Hence,In this paper,Realized GARCH model which error term follows NIG distribution,is used to fit the volatility and return distribution of Shanghai composite index.And then,the result is compared with another results when using Realized GARCH model which error term follows normal distribution,t distribution,skewed-t distribution respectively as well as GARCH model which error term follows normal distribution,t distribution,skewed-t distribution,NIG distribution respectively.Afterwards,according to different economic environments,this paper divides the samples in a more detailed way.The whole observation period is divided into four time phases: the pre-financial crisis period,the financial crisis period,the post-financial crisis period and the oscillation period of China's stock market.The empirical result shows that,in extreme cases,Realized GARCH-NIG model can describe the volatility of China's stock market much more accurately.The forcasting ability of Realized GARCH model is also superior to GARCH model,which reflects its superiority in risk simulation and prediction.Furthermore,compared to using the overall samples directly,modeling the data of different time phases gives more precise outcome of stock market's volatility.At the same time,after making a comparison between VaR and ES risk prediction results,it is found that ES risk measurement can make up the shortfall of VaR model when estimating the tail risk of the models based on fat-tailed distribution.