Journal of Risk Model Validation

Individual and flexible expected shortfall backtesting

Marcelo Brutti Righi and Paulo Sergio Ceretta


In this paper we propose an expected shortfall (ES) backtesting approach that uses the dispersion of a truncated distribution by the estimated value-at-risk (VaR) upper limit, does not limit the approach to the Gaussian case and allows us to test if each individual VaR violation is significantly different from the ES. Moreover, we present a Monte Carlo simulation algorithm to determine the significance of the backtest. We provide an empirical illustration that demonstrates the advantages that our backtests provide, especially the fact that there is no need to wait for a whole backtest period in order to prove the prediction that the ES test is inefficient.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

If you already have an account, please sign in here.

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here