Exponential Smoothing Methods of Forecasting and General ARMA Time Series Representations

Roland G. Shami and Ralph D. Snyder

No 267939, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: The focus of this paper is on the relationship between the exponential smoothing methods of forecasting and the integrated autoregressive-moving average models underlying them. In this paper we derive, for the first time, the general linear relationship between their parameters. A method, suitable for implementation on computer, is proposed to determine the pertinent quantities in this relationship. It is illustrated on common forms of exponential smoothing. It is also applied to a new seasonal form of exponential smoothing with seasonal indexes which always sum to zero.

Keywords: Research and Development/Tech Change/Emerging Technologies; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 15
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Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267939

DOI: 10.22004/ag.econ.267939

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