Over the past twenty years, damped trend exponential smoothing has performed well in numerous empirical studies, and it is now well established as an accurate forecasting method. The original motivation for this method was intuitively appealing, but said very little about why or when it provided an optimal approach. The aim of this paper is to provide a theoretical rationale for the damped trend method based on Brown's original thinking about the form of underlying models for exponential smoothing. We develop a random coefficient state space model for which damped trend smoothing provides an optimal approach, and within which the damping parameter can be interpreted directly as a measure of the persistence of the linear trend.
- time series
- state space models
- ARIMA models
- exponential smoothing
Mckenzie, E., & Gardner Jr, E. S. (2010). Damped trend exponential smoothing: A modelling viewpoint. International Journal of Forecasting, 26(4), 661-665. https://doi.org/10.1016/j.ijforecast.2009.07.001