Smooth Transition Exponential Smoothing

Taylor, James (2004) Smooth Transition Exponential Smoothing. Journal of Forecasting, 23 (6). pp. 385-404.


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.

Item Type: Article
Keywords: adaptive exponential smoothing, smooth transition, level shifts, outliers, management science
Subject(s): Management science
Date Deposited: 24 Jan 2012 20:16
Last Modified: 08 Aug 2018 12:46
Funders: N/A

Actions (login required)

Edit View Edit View