FORECASTING USING SIMPLE EXPONENTIAL SMOOTHING METHOD

In the paper a relatively simple yet powerful and versatile technique for forecasting time series data ‐ simple exponential smoothing is described. The simple exponential smoothing (SES) is a short-range forecasting method that assumes a reasonably stable mean in the data with no trend (consistent growth or decline). It is one of the most popular forecasting methods that uses weighted moving average of past data as the basis for a forecast. The procedure gives heaviest weight to more recent observations and smaller weight to observations in the more distant past. The accuracy of the SES method strongly depends on the optimal value of the smoothing constant a. To determine the optimal a value in the paper was used a traditional optimalization method based on the lowest mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE).