\section{Conclusion}

We have once again showed that the use of the conditional extreme value model is superior to a standard AR-GARCH model when it comes to estimating extreme quantiles of the return distribution. Though the improvement from using the ACER method compared to the POT method is relatively small, the conditional ACER method does consistently perform better than the POT method. The conditional method performs better than a stand alone POT and ACER, mostly because the quantile exceedances in this case are not well distributed and tend to cluster around high volatility periods. 