Extreme events are an important source of financial risk, but they present special challenges in quantitative forecasting.  In this paper we describe an empirical approach to forecasting extreme risk and evaluate its accuracy out-of-sample on a range of factor-based strategies and pair trades.  Our results show that for a large majority of strategies, our model is more consistent with market behavior than a conditional Normal model.