A note on upper bounds for forecast-value-added relative to naïve forecasts

 

In forecast value added analysis, the accuracy of relatively sophisticated forecasting methods is compared to that of naïve 1 forecasts to see whether the extra costs and effort of implementing them are justified. In this note, we derive a ratio that indicates the upper bound of a forecasting method’s accuracy relative to naïve 1 forecasts when the mean squared error is used to measure one-period-ahead accuracy. The ratio is applicable when a series is stationary or when its first differences are stationary. Formulae for the ratio are presented for several exemplar time series processes.

Cite

@article{fvanaive,
  author  = {Paul Goodwin and Fotios Petropoulos and Rob J Hyndman},
  doi     = {10.1057/s41274-017-0218-3},
  journal = {J the Operational Research Society},
  number  = {9},
  pages   = {1082-1084},
  title   = {A note on upper bounds for forecast-value-added relative to naïve forecasts},
  volume  = {68},
  year    = 2017
}