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.