Another look at forecast selection and combination: Evidence from forecast pooling

Another Look at Measures of Forecast Accuracy

We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition and the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be inadequate, and many of them are degenerate in commonly occurring situations. Instead, we propose that the mean absolute scaled error become the standard measure for ...

Another Look at Forecast-accuracy Metrics for Intermittent Demand

Preview: Some traditional measurements of forecast accuracy are unsuitable for intermittent-demand data because they can give infinite or undefined values. Rob Hyndman summarizes these forecast accuracy metrics and explains their potential failings. He also introduces a new metric—the mean absolute scaled error (MASE)—which is more appropriate for intermittent-demand data. More generally, he be...

Forecast Evaluation and Combination

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...

Forecast Combination across Estimation Windows∗

This paper considers the problem of forecast combination when forecasts are generated from the same model but use different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. The analysis is then extended to a linear regression model with an exogenous regressor. It is shown that compared to foreca...