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

Author

Listed:
  • Paul Goodwin

    (University of Bath)

  • Fotios Petropoulos

    (University of Bath)

  • Rob J. Hyndman

    (Monash University)

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.

Suggested Citation

  • Paul Goodwin & Fotios Petropoulos & Rob J. Hyndman, 2017. "A note on upper bounds for forecast-value-added relative to naïve forecasts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1082-1084, September.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:9:d:10.1057_s41274-017-0218-3
    DOI: 10.1057/s41274-017-0218-3
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    References listed on IDEAS

    as
    1. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    2. Steve Morlidge, 2014. "Using Relative Error Metrics to Improve Forecast Quality in the Supply Chain," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 34, pages 39-46, Summer.
    3. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

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