A Study Of Risk Measuring On China's SME Market And GE Market

With the development of China's stock market,it becomes a market including Main-Board,SME market and GE market.On one hand,SME market and GE market as important members of China's capital market.On the other hand,these markets feature in high price volatility and high risk which require a higher level of risk management than the others.How to measure the risks in China's SME market and GE market has become a study point in academia and industry.We assume that the return rate is subject to a normal distribution in a tranditional way.Howerever,some financial data with high kurtosis and fat tails have high volatility and occur extreme values.Consequently,we're likely underestimate the risk with the normal distribution assumption.EVT comes from engineering which applies in extreme value estimation.For VaR concerns about tail risk of asset,EVT is suitable for measuring VaR.Moreover,with Copula function,different assets can be connected together to form a joint distribution.Thus we can analyse the correlation between different assets while using Copula theory.Therefore Copula theory has been widely used in financial area.This paper focuses on China's SME market and GE market,sampling SME market index and GE market index of Shenzhen Stock Exchange,using GARCH model to describes volatility clustering which is not subject to normal distribution and EVT to describes tail risks of stock markets which exist high price volatility.With the help of these models,this paper calculated the VaR of SME market and GE market respectively.This paper applies different Copula models to analyse Va R of the portfolio by using MC simulation method.The results of the backtesing show that in a high confidence level,Clayton and mixed Copula are much accurate in measuring VaR of the portfolio.Finally,this paper uses mixed Copula to predict the portfolio's VaR in the next day to provide a reasonable number for risk management.