Smooth Test for Density Forecast Evaluation

Density forecast revisions and forecast efficiency

We explain that revisions to successive density forecasts of the same outcome, as measured by the Kullback-Leibler Information Criterion, need not be unpredictable, unlike those to conditional mean forecasts, even when the forecaster uses information efficiently. However one can still test the efficiency of fixed-event conditional density forecasts, similarly to conditional mean forecasts, by t...

Generalised Density Forecast Combinations *

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is try...

Density Forecast Combination

In this paper we investigate whether and how far density forecasts sensibly can be combined to produce a “better” pooled density forecast. In so doing we bring together two important but hitherto largely unrelated areas of the forecasting literature in economics, density forecasting and forecast combination. We provide simple Bayesian methods of pooling information across alternative density fo...

Path Forecast Evaluation

A forecast path refers to the vector of forecasts over the next 1 to h periods into the future. These forecasts are correlated across horizons so that to properly understand the uncertainty associated with the forecast path, one requires the joint predictive density of the path rather than the collection of marginal predictive densities for each horizon. This paper derives the joint predictive ...

Multiple forecast model evaluation∗