Value at risk calculations: An empirical analysis for stock market in China

This paper applies the extreme value theory on Value-at-Risk (VaR) calculation, which focuses on modeling the tails of the return distribution rather than the whole distribution. Extreme value theory has more meaning during the volatile market conditions, under which the distribution of returns almost has a fat tail. Because of its biggest advantage of comprehensive, VaR calculation has become the mainstream method of measuring risk. This paper deals with the behavior of the tails of financial series. More specifically, the focus is the use of extreme value theory to assess tail related risk. The application of extreme value theory is illustrated by an example from the Shanghai and Shenzhen stock market data. The paper concludes that the both distributions are fat tails and the limit distribution for centralized and normalized maxima is a Frechet type. So the extreme value theory is properly applied and it's a useful complement to traditional VaR methods.