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Recursive Models for Forecasting Seasonal Processes

Published online by Cambridge University Press:  19 October 2009

James E. Reinmuth  and
Dick R. Wittink
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Extract

Many of the typical problems encountered in forecasting a time series are alleviated when the series follows a seasonal pattern. The seasonal effect is independent of a long-term trend and cyclic effect. Furthermore, since the seasonal effect is recurrent and periodic, it is predictable. Thus, when the time series follows a seasonal pattern, the general shape of the series is known. Questions regarding the growth trend of the series, the expansion and contraction of the seasonal pattern, and random variation affecting the series are, however, left unanswered.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 9 , Issue 4 , September 1974 , pp. 659 - 684
Copyright
Copyright © School of Business Administration, University of Washington 1974

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