Empirical Comparison of Models for Short Range Forecasting

Results of a simulation study of the short-range forecasting effectiveness of exponentially smoothed and selected Box-Jenkins models for sixty-three monthly sales series are presented. Brown's exponentially smoothed constant, linear and six- and eight-term harmonic models are compared with two seasonal factor models and ten Box-Jenkins models. The seasonal factor models are Winters' three parameter model and a single parameter model developed by the author. The forecasting errors of the best of the Box-Jenkins models that were tested are either approximately equal to or greater than the errors of the corresponding exponentially smoothed models. Test results indicate that the four exponentially smoothed seasonal models yield approximately equivalent accuracy for most data series. If a sharply defined pattern exists, the seasonal factor models can yield smaller forecast errors than the harmonic models. If no seasonal pattern exists, the errors of the exponentially smoothed models with seasonal components are only slightly greater than those of the constant and linear models.

• 저널Management Science · 20(1) · 22–31
• 토픽Forecasting Techniques and Applications · Management Science and Operations Research
• DOI10.1287/mnsc.20.1.22
• 저자Gene K. Groff