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Exponential smoothing: the effect of initial values and loss functions on post-sample forecasting accuracy

Author: Makridakis, Spyros ; Hibon, MichèleINSEAD Area: Technology and Operations ManagementIn: International Journal of Forecasting, vol. 17, no.3, 1991 Language: EnglishDescription: p. 317-330.Type of document: INSEAD ArticleNote: Please ask the Library for this articleAbstract: This paper describes an empirical investigation aimed at measuring the effect of different initial values and loss functions (both symmetric and asymmetric) on the post-sample forecasting accuracy. The 1001 series of M-competition are used and three exponential smoothing methods are employed. The results are compared over various types of data and forecasting horizons and validated with additional data
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This paper describes an empirical investigation aimed at measuring the effect of different initial values and loss functions (both symmetric and asymmetric) on the post-sample forecasting accuracy. The 1001 series of M-competition are used and three exponential smoothing methods are employed. The results are compared over various types of data and forecasting horizons and validated with additional data

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