Model risk of expected shortfall - Lazar, Emese; Zhang, Ning (Journal of Banking & Finance, 2019)
In this paper we propose to measure the model risk of Expected Shortfall as the optimal correction needed to pass several ES backtests, and investigate the properties of our proposed measures of model risk from a regulatory perspective. Our results show that for the DJIA index, the smallest corrections are required for the ES estimates built using GARCH models. Furthermore, the 2.5% ES requires smaller corrections for model risk than the 1% VaR, which advocates the replacement of VaR with ES as recommended by the Basel Committee. Also, if the model risk of VaR is taken into account, then the corrections made to the ES estimates reduce by 50% on average.