An Empirical Research On Chinese Stock Market’s Risk Measure(VaR And CvaR) Based On GARCH Model

Along with the rapid enhancement of economic globalization, financial liberalization and China’s “Four Comprehensives” strategic blueprint, the economic system will be fully deepen with the financial market as the carrier of our economy playing an increasingly vital role in China’s economy. With the financial market is undergoing tremendous changes,measuring and preventing financial risks are turning into complex increasingly. The diversification of monetary policy for major economies, the rise of Internet-based financing as well as the maturity of financial engineering have not only change the overall financial architecture, but also exert a profound impact on financial volatility. Therefore,the measurement and management of the volatility in financial markets are urgently major issues which the financial institutions and investors pay common attention.In the wake of Chinese economy entering the new normal, China’s financial industry is also faced with new tasks including steady growth, promoting reform, structural adjustment, improvement of people’s livelihood and guards against risks. The key issue is how to seek a new balance among reform, development and stability. Under the background of China’s new normal, financial institutions and financial products are becoming more diversified, traditional financing and Internet financing are deeply integrated, thus the large pattern of our finance will make great strides toward internationalization. Financial markets refer to a huge system that contain different markets where the stock market as an important part having significant impacts on the financial markets. In the sense, it is necessary to undertake research on the volatility, asymmetry and spillover effect of China’s stock market.We choose the stock market as the main object of the study. This dissertation focuses on GARCH-class models and applies them to extract volatility feature from the daily returns in China’s main stock markets. Meanwhile, the linkages of stock markets among Shanghai and Shenzhen have been examined, and the volatility spillover effects are corroborated through the Granger casualty test. Finally, comparing VaR and CVaR estimations on the basis of the results of empirical research to extend the work of the dissertation. The findings from this research outline in the following three aspects. Firstly,GARCH-class models are able to capture the volatility features; Secondly, the spillover effects exist among two main stock markets but it may change dramatically; Thirdly, VaR and CVaR are efficient risk measures, however, for China’s financial market, the governmental intervention is an important factor to be considered.