China’s Commercial Banks Exchange Rate Risk Measurement Based On Marketization Of Exchange Rate Expectations

In July 2005, we began to use floating exchange rate system instead of the fixed exchange rate regime, which reference to a basket of currencies. The volatility and uncertainty of exchange rate makes the exchange rate risk of commercial banks become increasingly prominent. How to avoid exchange rate risk has become an important issue in the management of commercial banks. VaR method has become a mainstream method in risk measurement of the world, and it was widely used in global financial institutions and enterprises. In this paper, the VaR method is introduced to the empirical study of exchange rate risk measurement, and to explore its practical application in China’s financial market. This paper chose the dollar/RMB exchange rate, the euro/RMB exchange rate, yen/RMB exchange rate, HKD/RMB exchange rate and the pound/RMB exchange rate from July 25,2005 to December 31,2015 as the research object. At first the applicability of the model is tested on RMB exchange rate data of commercial bank, then The five group of logarithmic return series parameters are estimated by GARCH model, then selected two kinds of models which are suitable and calculate the VaR of each foreign currency returns, have the failure rate of test of VaR, obtains the optimal estimation model. The empirical results show that when measuring the RMB exchange rate risk, the confidence level should be 99%, the holding period should be 1 day. For dollar/RMB exchange rate, we should choose EGARCH (1,1)-GED, EG ARCH (1,1)-M-GED model as the best models. For the euro/RMB exchange rate, EGARCH (1, 1)-t model is best suitable. PARCH (1,1)-M-t can be established as the best model for HKD/RMB exchange rate. PARCH (1,1)-GED and TARCH (1,1)-GED have predictability for yen/RMB exchange rate. PARCH (1,1)-t and EGARCH (1,1)-GED can be established as the best models for pound/RMB exchange rate. Finally, the paper puts forward specific suggestions for exchange rate risk decision makers of commercial bank from two aspects of the method selection and system construction, to provide a reliable reference for improving the applicability and accuracy of VaR.