Value At Risk Measurement Research Based On Laplace Distribution

In 2007 the U.S. subprime mortgage crisis, and then evolved into the global financial crisis, financial risk control Once again become the focus of supervision, but financial risks and the key lies in the financial risk based. VaR(value-at-risk)method has become the mainstream for risk management and regulatory in the financial market.However, VaR and CVaR theory is not perfect, this article summarizes the basis of previous theory, combining the characteristics of financial risk (such as regression, volatility, a fat tail), put forward this article ARMA-GARCH-Laplace Model to measure the value of Chinese stock market VaR and CVaR. In this paper,1 January 1997 to April 15,2010 the Shanghai Composite Index and Shenzhen Component Index of the 3211 price index data for the sample,susing different distribution of the GARCH model to a measure of stock market risk, from the back testing results that the measurement model based on the Laplace distribution is better than the econometric models based on the traditional normal distribution, T distribution and the GED distribution, also confirmed China's stock market peak and fat tail features.