A simple combination of univariate models

Fotios Petropoulos and I have participated last year in M4 competition. Our approach performed well, finishing as 6th in the competition. This paper in International Journal of Forecasting explains what we used in our approach and why. Here’s the abstract:

This paper describes the approach that we implemented for producing the point forecasts and prediction intervals for our M4-competition submission. The proposed simple combination of univariate models (SCUM) is a median combination of the point forecasts and prediction intervals of four models, namely exponential smoothing, complex exponential smoothing, automatic autoregressive integrated moving average and dynamic optimised theta. Our submission performed very well in the M4-competition, being ranked 6th for the point forecasts (with a small difference compared to the 2nd submission) and prediction intervals and 2nd and 3rd for the point forecasts of the weekly and quarterly data respectively.

Paper in IJF.
Postprint of the paper.

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