Model Identification in Exponential Smoothing |
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Authors: | Everette S. Gardner Suffix" >Jr.,Ed. McKenzie |
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Affiliation: | 1.College of Business, University of Houston,USA;2.Mathematics Department,University of Strathclyde,UK |
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Abstract: | Model identification has traditionally been ignored in forecasting via exponential smoothing. The usual practice is to apply the same model to every time-series in a collection. This paper develops a procedure for model identification in large forecasting applications based on an examination of variances of differences of the time-series. The order of differencing yielding minimum variance suggests an appropriate model for the series. Empirical results show that this procedure selects models that give reasonable ex ante forecast accuracy. |
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