Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the...

The paper develops a model for combining point forecasts into a predictive distribution for a variable of interest. Our approach allows for point forecasts to be correlated and admits uncertainty on the distribution parameters given the forecasts. Further, it provides an easy way to compute an...

Probabilistic forecasts such as quantiles are essential inputs to decision-making under uncertainty. The most common type of forecasts often comes in the form of point forecasts, and it is therefore necessary for the decision maker to construct uncertainty measures around the obtained point...