Does a meta-combining method lead to more accurate forecasts in the decision-making process?

• Autorzy: Gulay Emrah , Aras Serkan

Identyfikatory

DOI

10.37190/ord240306

• Języki publikacji: EN

Abstrakty

EN

To improve forecasting accuracy, researchers employed various combination techniques for a long time. When researchers deal with time series data by using dissimilar models, the combined forecasts of these models are expected to be superior. Deriving a weighting scheme performing better than simple but hard−to−beat combining methods has always been challenging. In this study, a new weighting method based on the hybridisation of combining algorithms is proposed. Five popular datasets were utilised to demonstrate the effectiveness of the proposed method in an out-of-sample context. The results indicate that the proposed method leads to more accurate forecasts than other combining techniques used in the study.

Słowa kluczowe

EN

forecasting; combined forecasts; time series; meta-combining

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2024
• Tom: Vol. 34, No. 3
• Strony: 101--124
• Opis fizyczny: Bibliogr. 57 poz., rys.

Twórcy

autor

Gulay Emrah

• Department of Econometrics, Dokuz Eylul University, Turkey

• https://orcid.org/0000-0001-7825-333X

autor

Aras Serkan

• Department of Econometrics, Dokuz Eylul University, Turkey

• https://orcid.org/0000-0002-6808-3979

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).