Parameter Optimization

For forecast models with exponential smoothing, you can instruct the system to optimize the smoothing factors (see Forecast Parameters: Dependent on the Forecast Model).

If the system is instructed to optimize the smoothing factors, it calculates several parameter combinations and then selects the combination with the lowest mean absolute deviation (MAD). The finer the degree of optimization, the more exact, but also the more time-consuming, the parameter optimization. You can vary the increment (also known as the degree of optimization) from 0.1 (low), 0.2 (medium) and 0.3 (high).

If you have set the system correctly, it will carry out parameter optimization during initialization for the initial forecast as well as for all other forecasts. The most effective combination of the smoothing factors is determined by means of the ex-post forecast.

Please refer to Appendix B in this manual for additional information on the calculation of the MAD as well as the significance of the smoothing factors.

Optimizing the smoothing factor is only possible for models with the exponential smoothing procedure.