Publication: Electricity price forecasting by averaging dynamic factor models
dc.affiliation.dpto | UC3M. Departamento de Estadística | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: Técnicas no Paramétricas y de Computación Intensiva en Estadística | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: Modelización Estadística y Análisis de Datos | es |
dc.affiliation.instituto | UC3M. Instituto Flores de Lemus | es |
dc.contributor.author | Alonso Fernández, Andrés Modesto | |
dc.contributor.author | Bastos, Guadalupe | |
dc.contributor.author | García-Martos, Carolina | |
dc.contributor.funder | Ministerio de Economía y Competitividad (España) | es |
dc.date.accessioned | 2023-11-03T12:36:28Z | |
dc.date.available | 2023-11-03T12:36:28Z | |
dc.date.issued | 2016-08-01 | |
dc.description.abstract | In the context of the liberalization of electricity markets, forecasting prices is essential. With this aim, research has evolved to model the particularities of electricity prices. In particular, dynamic factor models have been quite successful in the task, both in the short and long run. However, specifying a single model for the unobserved factors is difficult, and it cannot be guaranteed that such a model exists. In this paper, model averaging is employed to overcome this difficulty, with the expectation that electricity prices would be better forecast by a combination of models for the factors than by a single model. Although our procedure is applicable in other markets, it is illustrated with an application to forecasting spot prices of the Iberian Market, MIBEL (The Iberian Electricity Market). Three combinations of forecasts are successful in providing improved results for alternative forecasting horizons. | en |
dc.description.sponsorship | Andrés M. Alonso acknowledges the support of the Ministry of Economy and Competitiveness, Spain, by Projects ECO2012-38442 and ECO2015-66593; Carolina García-Martos acknowledges financial support from Project DPI2011-23500, Ministry of Economy and Competitiveness, Spain; the authors would like to extend their appreciation to Professor Michael Wiper for his assistance and corrections regarding the proper use of English in this document. | en |
dc.format.extent | 21 | es |
dc.identifier.bibliographicCitation | Alonso, A., Bastos, G., & García‐Martos, C. (2016). Electricity price forecasting by averaging dynamic factor models. Energies, 9(8), 600. | en |
dc.identifier.doi | https://doi.org/10.3390/en9080600 | |
dc.identifier.issn | 1996-1073 | |
dc.identifier.publicationfirstpage | 1 | es |
dc.identifier.publicationissue | 8, 600 | es |
dc.identifier.publicationlastpage | 21 | es |
dc.identifier.publicationtitle | Energies (Energies) | en |
dc.identifier.publicationvolume | 9 | es |
dc.identifier.uri | https://hdl.handle.net/10016/38755 | |
dc.identifier.uxxi | AR/0000018274 | |
dc.language.iso | eng | es |
dc.publisher | MDPI | en |
dc.relation.projectID | Gobierno de España. ECO2012-38442 | es |
dc.relation.projectID | Gobierno de España. ECO2015-66593 | es |
dc.relation.projectID | Gobierno de España. DPI2011-23500 | es |
dc.rights | © 2016 by the authors; licensee MDPI, Basel, Switzerland | en |
dc.rights | Atribución 3.0 España | * |
dc.rights.accessRights | open access | en |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject.eciencia | Estadística | es |
dc.subject.other | Market | en |
dc.subject.other | Combination | en |
dc.subject.other | Dimension | en |
dc.subject.other | Selection | en |
dc.subject.other | Dimensionality reduction | en |
dc.subject.other | Electricity prices | en |
dc.subject.other | Bayesian model averaging | en |
dc.subject.other | Forecast combination | en |
dc.title | Electricity price forecasting by averaging dynamic factor models | en |
dc.type | research article | * |
dc.type.hasVersion | VoR | * |
dspace.entity.type | Publication |
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