What options exist in order to forecast when next observation will be an outlier in a time series? Initially, I thought to train a simple forecasting model, which turned out to decently predict the normal values, but not predict the outliers, which I am more interested in for business purposes. Note that I want to predict when next observation will be anomalous, not detect previously anomalous observation.
I cant find any literature about this topic online. Am I just not capturing some feature that might prove a better predictor or is there some methodology that may help?