Details

Autor(en) / Beteiligte

• Poler, Raul
• Mula, Josefa

Titel

Forecasting model selection through out-of-sample rolling horizon weighted errors

Ist Teil von

• Expert systems with applications, 2011-11, Vol.38 (12), p.14778-14785

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2011

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• ► Expert system for time series forecasting model selection. ► Good performance with M3 Competition time series. ► Successfully applied to a real case. Demand forecasting is an essential process for any firm whether it is a supplier, manufacturer or retailer. A large number of research works about time series forecast techniques exists in the literature, and there are many time series forecasting tools. In many cases, however, selecting the best time series forecasting model for each time series to be dealt with is still a complex problem. In this paper, a new automatic selection procedure of time series forecasting models is proposed. The selection criterion has been tested using the set of monthly time series of the M3 Competition and two basic forecasting models obtaining interesting results. This selection criterion has been implemented in a forecasting expert system and applied to a real case, a firm that produces steel products for construction, which automatically performs monthly forecasts on tens of thousands of time series. As result, the firm has increased the level of success in its demand forecasts.