[smokel]

This article focuses mostly on point forecasting. There are many other things that are interesting to forecast.

Consider for example the use case of forecasting the average speed on a road segment with a maximum speed of 70mph. Forecasting whether that will be 69.8 or 70.3 is not very relevant. What is relevant is forecasting when the speed drops below a traffic jam threshold. But the exact timing of that might be impossible to forecast due to the inherently chaotic behavior of traffic. Forecasting the probability of a traffic jam occurring may be more interesting to practitioners.

[t0mpr1c3]

Indeed. For example, volatility is of interest in financial data, because it relates to the pricing of risk. So are the correlations between asset classes.

Interestingly market volatility often goes hand-in-hand with increased correlation between asset prices: https://en.wikipedia.org/wiki/Anna_Karenina_principle#Order_...

This corresponds to a restatement of Murphy's Law, namely "life is a bitch and then you die". When you most need a diversified portfolio, diversification is hardest to achieve.