Computing VaR and ES Based on the Extreme Value Theory:A Case Study of ZTE Data
Ding Xin-yu · Journal of Guangxi Normal University · 2015
Value at Risk(VaR)is an important measurement tool for market risk.The Block Maxima Model(BMM)and the Peak Over Threshold(POT)model are employed to compute the VaR and Expected Shortfall(ES)for ZTE return data with heavy tails respectively.A discrepancy measure is proposed to select the threshold for the POT model.The data analysis shows that applying the extreme value theory in risk measurement can fully capture information from the tail of data and obtain reasonable VaR and ES to satisfy actual needs,and the results from the POT model are more stable than the ones from BMM.