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Why the damped trend works

Author

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  • E S Gardner

    (University of Houston)

  • E McKenzie

    (University of Strathclyde)

Abstract

The damped trend method of exponential smoothing is a benchmark that has been difficult to beat in empirical studies of forecast accuracy. One explanation for this success is the flexibility of the method, which contains a variety of special cases that are automatically selected during the fitting process. That is, when the method is fitted, the optimal parameters usually define a special case rather than the method itself. For example, in the M3-competition time series, the parameters defined the damped trend method only about 43% of the time using local initial values for the method components. In the remaining series, a special case was selected, ranging from a random walk to a deterministic trend. The most common special case was a new method, simple exponential smoothing with a damped drift term.

Suggested Citation

  • E S Gardner & E McKenzie, 2011. "Why the damped trend works," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1177-1180, June.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:6:d:10.1057_jors.2010.37
    DOI: 10.1057/jors.2010.37
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    References listed on IDEAS

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    1. Hyndman, Rob J. & Billah, Baki, 2003. "Unmasking the Theta method," International Journal of Forecasting, Elsevier, vol. 19(2), pages 287-290.
    2. Everette S. Gardner, Jr. & Ed. Mckenzie, 1985. "Forecasting Trends in Time Series," Management Science, INFORMS, vol. 31(10), pages 1237-1246, October.
    3. Armstrong, J. Scott & Fildes, Robert, 2006. "Making progress in forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 433-441.
    4. Flores, Benito E. & Pearce, Stephen L., 2000. "The use of an expert system in the M3 competition," International Journal of Forecasting, Elsevier, vol. 16(4), pages 485-496.
    5. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    5. Gardner, Everette S., 2015. "Conservative forecasting with the damped trend," Journal of Business Research, Elsevier, vol. 68(8), pages 1739-1741.
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    7. Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
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    11. Li, Qinyun & Disney, Stephen M. & Gaalman, Gerard, 2014. "Avoiding the bullwhip effect using Damped Trend forecasting and the Order-Up-To replenishment policy," International Journal of Production Economics, Elsevier, vol. 149(C), pages 3-16.
    12. Ferbar Tratar, Liljana & Mojškerc, Blaž & Toman, Aleš, 2016. "Demand forecasting with four-parameter exponential smoothing," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 162-173.
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