Smooth transition exponential smoothing

Smooth transition exponential smoothing

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Article ID: iaor2008515
Country: United Kingdom
Volume: 23
Issue: 6
Start Page Number: 385
End Page Number: 404
Publication Date: Sep 2004
Journal: International Journal of Forecasting
Authors:
Abstract:

Adaptive exponential smoothing methods allow a smoothing parameter to change over time, in order to adapt to changes in the characteristics of the time series. However, these methods have tended to produce unstable forecasts and have performed poorly in empirical studies. This paper presents a new adaptive method, which enables a smoothing parameter to be modelled as a logistic function of a user-specified variable. The approach is analogous to that used to model the time-varying parameter in smooth transition models. Using simulated data, we show that the new approach has the potential to outperform existing adaptive methods and constant parameter methods when the estimation and evaluation samples both contain a level shift or both contain an outlier. An empirical study, using the monthly time series from the M3-Competition, gave encouraging results for the new approach.

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