Exponential Smoothing: A Prediction Error Decomposition Principle
AbstractIn the exponential smoothing approach to forecasting, restrictions are often imposed on the smoothing parameters which ensure that certain components are exponentially weighted averages. In this paper, a new general restriction is derived on the basis that the one-step ahead prediction error can be decomposed into permanent and transient components. It is found that this general restriction reduces to the common restrictions used for simple, trend and seasonal exponential smoothing. As such, the prediction error argument provides the rationale for these restrictions.
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Bibliographic InfoPaper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 15/04.
Length: 10 pages
Date of creation: Aug 2004
Date of revision:
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Web page: http://www.buseco.monash.edu.au/depts/ebs/
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Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-09-05 (All new papers)
- NEP-ECM-2004-09-05 (Econometrics)
- NEP-ETS-2004-09-05 (Econometric Time Series)
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