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dc.contributor.authorCiarreta Antuñano, Aitor ORCID
dc.contributor.authorMuniain Izaguirre, Peru
dc.contributor.authorZárraga Alonso, Ainhoa ORCID
dc.date.accessioned2022-11-30T18:08:04Z
dc.date.available2022-11-30T18:08:04Z
dc.date.issued2022-11
dc.identifier.citationElectric Power Systems Research 212 : (2022) // Article ID 108144es_ES
dc.identifier.issn0378-7796
dc.identifier.issn1873-2046
dc.identifier.urihttp://hdl.handle.net/10810/58629
dc.description.abstractThis paper analyzes the potential for including jumps and cojumps in electricity price forecasting models. The study is carried out on the German-Austrian day-ahead electricity market with a multivariate framework in which each hour of the day is treated as an individual time series. Three models are specified: The ARX model, the ARX-J model (which includes jumps), and the ARX-J-CJ model (which also includes cojumps). Prices are transformed using several variance stabilizing transformations. The forecasting performance of the three models with original and transformed prices is compared using several forecast horizons running from one day-ahead to one week-ahead. Results show that the forecast horizon is crucial in determining whether jumps and cojumps should be included in electricity price forecasting. Jumps and cojumps add important information to forecast prices for horizons longer than 4 days, but there is no gain in forecast accuracy for shorter horizons. The results are of interest to market participants for taking optimal decisions and pricing base week futures contracts.es_ES
dc.description.sponsorshipFinancial support from Dpto. de Educación del Gobierno Vasco, Spain under research grant IT1336-19 and from Ministerio de Ciencia e Innovación, Spain under research grant PID2019-108718GB-I00 is acknowledged. Open access funding provided by the University of the Basque Country.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/PID2019-108718GB-I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectprice forecastinges_ES
dc.subjectjumpses_ES
dc.subjectcojumpses_ES
dc.subjectelastic netes_ES
dc.subjectvariance stabilizing transformationses_ES
dc.titleDo jumps and cojumps matter for electricity price forecasting? Evidence from the German-Austrian day-ahead marketes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/)es_ES
dc.rights.holderAtribución-NoComercial-SinDerivadas 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0378779622003650?via%3Dihubes_ES
dc.identifier.doi10.1016/j.epsr.2022.108144
dc.departamentoesAnálisis Económicoes_ES
dc.departamentoesMétodos Cuantitativoses_ES
dc.departamentoesMatemática aplicadaes_ES
dc.departamentoeuAnalisi Ekonomikoaes_ES
dc.departamentoeuMetodo Kuantitatiboakes_ES
dc.departamentoeuMatematika aplikatuaes_ES


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© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/)
Except where otherwise noted, this item's license is described as © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/)