Abstract
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.
Original language | English |
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Pages (from-to) | 1082-1084 |
Number of pages | 3 |
Journal | Journal of the Operational Research Society |
Volume | 68 |
Issue number | 9 |
DOIs | |
Publication status | Published - Sep 2017 |
Keywords
- ARIMA models
- forecast accuracy
- forecasting