On the optimal prediction of extreme events in heavy-tailed time series with applications to solar flare forecasting
重尾时间序列极端事件的最优预测及太阳耀斑预报应用
The prediction of extreme events in time series is a fundamental problem arising in many financial, scientific, engineering, and other applications. We begin by establishing a general Neyman-Pearson-type characterization of optimal extreme event predictors in terms of density ratios. This yields new insights and several closed-form optimal extreme event predictors for additive models. These results naturally extend to time series, where we study optimal extreme event…