Application Research Of Copula And Monte Carlo Method In Portfolio Risk Measurement

This paper comprehensively introduces model theory of VaR, presents its producing background, research status, basic principle, calculation process and methods. The Copula function is systematically analyzed and summarized. According to the deficiency for linear correlation that is analyzed by known analysis method, the paper introduces Copula function to depict correlation structure for different assets in portfolio to make a more precise measurement for portfolio risk.In empirical aspects, this paper is based on Shanghai stock index and Shenzhen index component portfolio for research object, and takes closing price from Jan.25th,2010to Dec.28th,2012as the valid data. By comparing the empirical results,it can draw conclusion that the two kinds of Copula Function selection methods are feasible, indeed using the preferred Copula Function to establish Copula-VaR-GARCH model, also for Copula applications in portfolio risk research provides a new idea.The paper use Copula-VaR-GARCH model to imitate financial time series and compute VaR by Monte Carlo simulation, taking into account the income of China’s securities market distribution rate sequence of non normality, using both to be able to describe the time-varying variance can reflect the distribution of the rate of return of the peak, Calculating the market index and thick tail characteristics GARCH model of VaR value. At last, this paper gives summary on Copula methods in the application of risk research, Studying on stock market volatility (risk) and the relationship between expected return has important theoretical significance and practical value.