VaR Model Based on GARCH Approach and Extreme Value Theory with Application in Chinese Interbank Offering Market

Value at Risk (VaR) has become the standard measure that financial analysts use to quantify market risk. VaR is defined as the maximum potential change in value of financial instruments with a given probability over a certain horizon. In this paper, we firstly combine GARCH-GJR model with extreme value theory to describe the statistical features of returns series of Shanghai Interbank Offered Rate (SHIBOR). Then, POT method was used to analyze the innovations and estimate the VaR and ES. Through back testing, we find that our model is suitable to measure the systematic risk in the interbank offering market in China, which could help to analyze the interest rate risk, trends and causes of changes of Chinese interest market.