Research On VaR Of Shanghai And Shenzhen Stock Based By T-Copula-EGARCH Model

As financial derivatives and information technology developing, the trading volume of global financial market rise quickly. However, there is no such thing as a free lunch. Risk of market, such as the2007U.S. subprime mortgage crisis, the Greek debt crisis at the end of2009brought huge losses to investors. So it becomes an important issue for the various financial institutions that how to effectively calculate the risk value of financial asset. Typically, there are three main types of methods used by scholars:sensitivity analysis, historical income simulation, Monte Carlo simulation method. It’s easy to calculate the VaR of the individual financial assets, but it’s difficult to calculate the VaR of portfolios under condition of joint distribution of financial assets. In the past, much more scholars usually calculate the value at risk under the assumption that financial assets obey the linear correlation. On the contrary, multiple financial assets do not obey the linear correlation. For this reason, my essay introduced the Copula theory to describe the multiple correlations of financial assets. In the empirical part, I conducted time series analysis to found EGARCH model described volatility and leverage characteristics of Shanghai and Shenzhen stock market with the data from January15th,2008to August20th,2012. Then, I conducted European square distance method to describe the dependency of the Shanghai and Shenzhen stock market with a suitable t-Copula function. At last, I used the Monte Carlo simulation method, t-Copula-GARCH model, t-Copula-EGARCH model to build model, to compare the VaRs calculated. As a consequence, T-Copula-EGARCH’s VaR is the most realistic one.