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Another look at forecast selection and combination: Evidence from forecast pooling
Department of Management Science, Lancaster University Management School, Lancaster University, United Kingdom.ORCID-id: 0000-0003-0211-5218
Faculty of Business, Environment and Society, Coventry University, United Kingdom.
School of Management, University of Bath, United Kingdom.
2019 (Engelska)Ingår i: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 209, s. 226-235Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Forecast selection and combination are regarded as two competing alternatives. In the literature there is substantial evidence that forecast combination is beneficial, in terms of reducing the forecast errors, as well as mitigating modelling uncertainty as we are not forced to choose a single model. However, whether all forecasts to be combined are appropriate, or not, is typically overlooked and various weighting schemes have been proposed to lessen the impact of inappropriate forecasts. We argue that selecting a reasonable pool of forecasts is fundamental in the modelling process and in this context both forecast selection and combination can be seen as two extreme pools of forecasts. We evaluate forecast pooling approaches and find them beneficial in terms of forecast accuracy. We propose a heuristic to automatically identify forecast pools, irrespective of their source or the performance criteria, and demonstrate that in various conditions it performs at least as good as alternative pools that require additional modelling decisions and better than selection or combination. 

Ort, förlag, år, upplaga, sidor
Elsevier, 2019. Vol. 209, s. 226-235
Nyckelord [en]
Cross-validation, Forecast combination, Forecast pooling, Forecasting, Model selection, Lakes, Uncertainty analysis, Cross validation, Forecast accuracy, Forecast combinations, Forecast errors, Modelling process, Performance criterion, Weighting scheme
Nationell ämneskategori
Sannolikhetsteori och statistik Annan elektroteknik och elektronik Meteorologi och atmosfärforskning
Identifikatorer
URN: urn:nbn:se:his:diva-18236DOI: 10.1016/j.ijpe.2018.05.019ISI: 000464087900023Scopus ID: 2-s2.0-85047273712OAI: oai:DiVA.org:his-18236DiVA, id: diva2:1399243
Tillgänglig från: 2020-02-27 Skapad: 2020-02-27 Senast uppdaterad: 2020-03-02Bibliografiskt granskad

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Kourentzes, Nikolaos

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International Journal of Production Economics
Sannolikhetsteori och statistikAnnan elektroteknik och elektronikMeteorologi och atmosfärforskning

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Totalt: 124 träffar
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