Traditionally, the quality of a forecasting model is judged by how it compares, in terms of accuracy, to alternative models. However, by providing a relative measure, no indication is given as to how much scope there might be for improvements beyond the benchmark model. When judgemental methods...

A large literature has evolved in the thirty years since the seminal work on combining forecasts. Despite this, when evaluating performance we only look at measures of accuracy and thus ignore most of the rigour of time series analysis. Furthermore, the output from a combination of forecasts is...

Exponential smoothing methods do not involve a formal procedure for identifying the underlying data generating process. The issue is then whether prediction intervals should be estimated by a theoretical approach, with the assumption that the method is optimal in some sense, or by an empirical...

Despite a considerable literature on the combination of forecasts, there is little guidance regarding the assessment of their uncertainty. Since combining methods do not involve a formal procedure for identifying the underlying data generating model, theoretical variance expressions are not...

A novel proposal for combining forecast distributions is to use quantile regression to combine quantile estimates. We consider the usefulness of the resultant linear combining weights. If the quantile estimates are unbiased, then there is strong intuitive appeal for omitting the constant and...

Forecasting category or industry sales is a vital component of a company's planning and control activities. Sales for most mature durable product categories are dominated by replacement purchases. Previous sales models which explicitly incorporate a component of sales due to replacement assume...