Management Science · 1985 · 388 citations · 2 references
Forecasting MethodologyEconomic ForecastingEngineeringBusiness ForecastingData ScienceMacroeconomicsPredictive AnalyticsForecast AccuracyEconometricsBusinessTrend PredictionForecastingForecast Lead TimeTrend AnalysisStatisticsTime Series AnalysisNonlinear Time Series
Most time series methods assume trends persist indefinitely, regardless of forecast horizon. The study develops an exponential smoothing model to damp erratic trends. The model is tested on 1,001 time series originally analyzed by Makridakis et al. The model improves forecast accuracy over linear trend smoothing, especially at long lead times, and outperforms sophisticated models such as those of Lewandowski and Parzen.
Most time series methods assume that any trend will continue unabated, regardless of the forecast lead time. But recent empirical findings suggest that forecast accuracy can be improved by either damping or ignoring altogether trends which have a low probability of persistence. This paper develops an exponential smoothing model designed to damp erratic trends. The model is tested using the sample of 1,001 time series first analyzed by Makridakis et al. Compared to smoothing models based on a linear trend, the model improves forecast accuracy, particularly at long leadtimes. The model also compares favorably to sophisticated time series models noted for good long-range performance, such as those of Lewandowski and Parzen.
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An Analysis of General Exponential Smoothing
Ed McKenzie · Operations Research · 1976 · 19 citations
Forecasting Methodology, Forecasting Systems, Engineering +15