Financial Market Risk Research Based On MC-GARCH-VaR

As the development of stock index futures and mechanism for short sell-ing securities, the securities market is tend to be perfect. The stock market, as one important part in our whole country economy, its status and role has become more and more prominent. At the same time, our financial market is still in a transitional stage, when the money market and capital market have obvious fluctuations. On this special time, the risk management in finance need to be strengthened immediately. In order to enhance the competitiveness of our financial market, the capacity to resist risk, we must grasp the risk measurement, risk prediction capacity so that we can manage and monitor our financial market.As I have worked for some different financial institutions for a long time. In this paper I will use my view of our financial market present situation to elaborate the calculation step of some traditional VaR mentions with practical significance. This is also a innovation in this paper.VaR method has been widely used in measuring financial market risk. We often assume that the market rate of return follows a normal distribution in the traditional VaR method, but this hypothesis has been verified as not practical in foreign financial market. In this paper I analyze the HS300index logarithm yield from June9.2005to December29.2011, and I find the time series have obvious sharp peak and fat-tail, heteroscedasticity and so on. Naturally, we take into account the use of. GARCH model to simulate this financial time series. I simulate the financial time series by GARCH. EGARCH. TARCH. EGARCH-M, TARCH-M and so on. As results confirm, the GARCH(1,1) model can relatively simulate the financial time series well. We can use Monte-Carlo simulation to predict the next yield and then we can get corresponding VaR. After that, we can use Kupiec back testing to test our result. At last, we can compare the result with history simulation method and normal mothod before. We can find easily that MC-GARCII-VaR. method have improved a lot in efficiency. and has strong stability.