Introduction to exceedance probability forecasting

This recipe introduces exceedance probability forecasting problems. Exceedance events occur when a time series exceeds a predefined threshold in a predefined future period. This problem is relevant when the tails of the time series distribution can have a significant impact on the domain. For example, consider the case of the inflation rate in the economy. Central banks leverage this type of forecast to assess the possibility that the inflation rate will exceed some critical threshold, above which they might consider increasing interest rates.

From a data science perspective, exceedance events are binary problems. Thus, it is common to tackle them using binary probabilistic classification models. One of the challenges is that the class representing the exceedance events is rare, which makes the learning task more difficult.

Getting ready

We’ll use a multivariate time series as an example to describe what an exceedance...