An approach for selecting times series forecasting models

A method is developed for evaluating forecasting models with respect to both error and complexity in forecasting. Several types of forecasting accuracy measures (MSE, MPE, MAPE, Theil’s U-Statistic and a loss cost function) are examined and the approach is illustrated using short-term forecasting methods, and weekly and four-weekly data. The approach can, however, be applied equally to immediate, medium- and long-term forecasting.