关键词: VaR模型, CVaR模型, 股市风险, 沪深300指数, GARCH簇模型

Abstract: In the study of the financial risk measurement model, the crucial task is to accurately measure the volatility of the financial income sequence,and the measurement of the volatility of the financial return is directly related to accurate evaluation of the risk value. VaR model and CVaR model serve as important tools of financial risk measurement, but they are seldom applied to the study of stock market risk. The VaR model measures risk with mathematical statistics, a method which boasts wide adaptability but has disadvantages in calculation. CVaR model features simple calculation but high accuracy and validity. This paper selects the closing price data of the Shanghai and Shenzhen 300 index, and estimates the volatility of the yield sequence through the GARCH cluster model based on the different distribution conditions, and then calculates the VaR value and the CVaR value after comparing the different GARCH models. Then the VaR model and the CVaR model are compared and analyzed. The results show that the CVaR value always exceeds the VaR value at the same confidence level; when VaR value fails in measuring risk, CVaR value can better measure risk loss, thus making up the defect of VaR value.

Key words: VaR model, CVaR model, stock market risk, the Shanghai and Shenzhen 300 index, GARCH cluster model