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Dynamics of Exponential Smoothing with Trend and Seasonal Terms

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  • John O. McClain

    (Cornell University)

Abstract

The characteristics of seasonally adjusted, exponentially smoothed forecasts are studied through the frequency response and impulse response functions. The appropriateness of using exponential smoothing for updating the seasonal base series is called into question, due to its tendency to store random noise for long periods. Exponential smoothing with trend is also examined. It is concluded that Brown's formulation has the property of being critically damped, so that its response to changes in the time series under study is the most rapid possible without overshoot.

Suggested Citation

  • John O. McClain, 1974. "Dynamics of Exponential Smoothing with Trend and Seasonal Terms," Management Science, INFORMS, vol. 20(9), pages 1300-1304, May.
    • Handle: RePEc:inm:ormnsc:v:20:y:1974:i:9:p:1300-1304
    DOI: 10.1287/mnsc.20.9.1300
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    Cited by:

    1. Alejandro Toriello & George Nemhauser & Martin Savelsbergh, 2010. "Decomposing inventory routing problems with approximate value functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(8), pages 718-727, December.
    2. Francisco J. Díaz-Borrego & María del Mar Miras-Rodríguez & Bernabé Escobar-Pérez, 2019. "Looking for Accurate Forecasting of Copper TC/RC Benchmark Levels," Complexity, Hindawi, vol. 2019, pages 1-16, April.
    3. Godfrey, Gregory A. & Powell, Warren B., 2000. "Adaptive estimation of daily demands with complex calendar effects for freight transportation," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 451-469, August.
    4. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.

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