Volatility And Risk Of Chinese Stock Market

With the development of financial theory, modern risk management, modern portfolio theory and variety of financial derivatives and instruments, the volatility of the stock market index return also becomes important, and the volatility of stock market is been increasingly concerned. The Chinese stock market is an emerging market, and the frequency of fluctuation becomes bigger and bigger because of the short time, because of the affections from the external world, so it is very important to examine the sudden changes in volatility of Chinese stock market, in order to know the characteristic of fluctuation of the stock indices and, to research what factors have broken out them. Return of financial assets often goes with risk, so that we all want to minimize the risk or maximize the return. Therefore, measures of risk of financial assets have been popular for a long time.In this paper, we focus on these two problems based on the previous studies.This article is divided into two parts. The first part is about the examination and fitting of fluctuations.Firstly, we choose the Iterative Cumulative Sum of Squares (ICSS) algorithm and the Exponentially Weighted Moving Average (EWMA) algorithm to study the Shanghai Composite Index and the Shenzhen Component Index, then it is found that under similar circumstances in the results, EWMA algorithm is simpler than ICSS algorithm as well as easier to operate. This article chooses results of EWMA algorithm to the further study.Secondly, put the change-points as dummy variables into GARCH model. The results show that Chinese stock market becomes more mature and more stable after Dec.16,1996, and the correlation between Shanghai and Shenzhen market has been strengthened,comparing with no dummy variables in GARCH model.The second part is on measures of risk on the stock market. Value at Risk (VaR) is a commonly used measure of risk indicators. Variance-covariance method is the common method of calculating VaR. Here EWMA algorithm is used to estimate the variance, to calculate VaR. It is found that the VaR obtained here can be used to measure the risk of Chinese stock market. Also, after removing the change-point, the VaR value calculated is smoother, indicating that the change-point in the second chapter is valid.