Template-type: ReDIF-Paper 1.0
Author-Name: Jennifer L. Castle
Author-Workplace-Name: Magdelen College, University of Oxford
Author-Email: jennifer.castle@magd.ox.ac.uk
Author-Name: Jurgen A. Doornik
Author-Workplace-Name: Nuffield College, University of Oxford
Author-Email: jurgen.doornik@nuffield.ox.ac.uk
Author-Name: David Hendry
Author-Workplace-Name: Nuffield College, University of Oxford
Author-Email: david.hendry@nuffield.ox.ac.uk
Title: Some forecasting principles from the M4 competition
Abstract: Economic forecasting is difficult, largely because of the many sources of nonstationarity. The M4 competition aims to improve the practice of economic forecasting by providing a large data set on
which the efficacy of forecasting methods can be evaluated. We consider the general principles that seem to be the foundation for successful forecasting, and show how these are relevant for methods that do well in M4. We establish some general properties of the M4 data set, which we use to improve the basic benchmark methods, as well as the Card method that we created for our submission to the
M4 competition. A data generation process is proposed that captures the salient features of the annual data in M4.
Keywords: Automatic forecasting, Calibration, Prediction intervals, Regression, M4, Seasonality, Software, Time series, Unit roots
Length: 27 pages
Creation-Date: 2019-01-09
Number: 2019-W01
File-URL: https://www.nuffield.ox.ac.uk/economics/Papers/2019/2019W01_M4_forecasts.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:1901