Mostrar el registro sencillo del ítem

dc.creatorArango M.
dc.creatorDíaz J.
dc.creatorRamírez Y.
dc.date2020
dc.date.accessioned2021-02-05T14:58:17Z
dc.date.available2021-02-05T14:58:17Z
dc.identifier.issn16469895
dc.identifier.urihttp://hdl.handle.net/11407/5958
dc.descriptionForecasting the price of electric energy is of the utmost importance for entrepreneurs, academics and regulators, as this market is essential for the economic development of the countries. Its forecast is a challenge, since it is a basic product that has high levels of volatility, because its behavior depends on the climate, the price of fuels and the limitations for its storage. For this reason, a method is proposed to forecast the price of electricity in the Colombian market, based on economic models; ARIMA-GARCH. Through the statistics, it was concluded that the model of mayor adjustment for the variation of the price in media is an ARMA (14.10)–GARCH (1.1), indicating that the decision makers will consider the results of the last 14 days to design your investment strategies. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.
dc.language.isospa
dc.publisherAssociacao Iberica de Sistemas e Tecnologias de Informacao
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85080990923&partnerID=40&md5=26ecf073946c4f04935791f779a12ece
dc.sourceRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
dc.subjectARIMA-GARCH modelspa
dc.subjectElectricity price forecastspa
dc.titleForecast of the energy price in colombia: An econometric application [Pronóstico de precio energético em colombia: Una aplicación econométrica]
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería Financieraspa
dc.relation.citationvolume2020
dc.relation.citationissueE27
dc.relation.citationstartpage663
dc.relation.citationendpage676
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationArango, M., Investigadora Docente Universidad de Medellín, Docente Universidad Nacional de Colombia, Medellín, 050026, Colombia
dc.affiliationDíaz, J., Investigador Universidad Autónoma de Bucaramanga, Bucaramanga, Colombia
dc.affiliationRamírez, Y., Estudiante Maestría en Finanzas, Universidad de Medellín, Medellín, 050026, Colombia
dc.relation.referencesBalza, L., Espinasa, R., Serebrisky, T., ¿Luces encendidas? Necesidades de Energía para América Latina y el Caribe al 2040 (2016) Banco Interamerciano De Desarrollo, (378), p. 39. , https://publications.iadb.org/handle/11319/7361, Retrieved from
dc.relation.referencesBarrientos, J., Tabares, E., Velilla, E., Forecasting electricity price in Colombia: A comparison between neural network, ARMA process and hybrid models (2018) International Journal of Energy Economics and Policy, 8 (3), pp. 97-106
dc.relation.referencesCastillo, Y., Castrillón Gutiérrez, M., Vanegas-Chamorro, M., Valencia, G., Villicaña, E., Rol de las Fuentes No Convencionales de Energía en el sector eléctrico colombiano (2015) Prospectiva, 13 (1), p. 39. , https://doi.org/10.15665/rp.v13i1.358
dc.relation.referencesDíaz Contreras, J.A., Macías Villalba, G.I., Luna González, E., Estrategia de cobertura con productos derivados para el mercado energético colombiano (2014) Estudios Gerenciales, 30 (130), pp. 55-64. , https://doi.org/10.1016/j.estger.2014.02.008
dc.relation.referencesInteramericano, E.B., Energía y desarrollo económico en América Latina. (2002) Bolentin Economico De Ice, pp. 31-44
dc.relation.referencesArango, M.A.A., Botero, S.B., The application of real options as a tool for decision-making in the electricity market (2017) 12Th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1-6. , https://doi.org/
dc.relation.referencesMarín, J.A.V., (2017) Proyección De La Demanda De energía eléctrica Y Potencia máxima En Colombia, p. 32
dc.relation.referencesMonsegny, M.C., Cuervo, E.C., Arch, M., Egarch, G.Y., Series, A.A., Modelos ARCH, GARCH Y EGARCH: Aplicaciones a Series Financieras (2008) Cuadernos De Economía, 27, pp. 287-320
dc.relation.referencesMuñoz-Santiago, A., Pronosticos Del Precio De La Energia en Colombia utilizando modelos ARIMA con IGARCH (2017) Revista De Economía Del Rosario, 20 (1), pp. 127-161
dc.relation.referencesRueda, V.M., Velásquez, J.D., Franco, C.J., Avances recientes en la predicción de la demanda de electricidad usando modelos no lineales (2011) Dyna, 167, pp. 36-43. , http://www.scielo.org.co/pdf/dyna/v78n167/a04v78n167.pdf, Retrieved from
dc.relation.referencesTan, Z., Zhang, J., Wang, J., Xu, J., Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models (2010) Applied Energy, 87 (11), pp. 3606-3610. , https://doi.org/10.1016/j.apenergy.2010.05.012
dc.relation.referencesTang, E., Peng, C., Xu, Y., Changes of energy consumption with economic development when an economy becomes more productive (2018) Journal of Cleaner Production, 196, pp. 788-795. , https://doi.org/10.1016/j.jclepro.2018.06.101
dc.relation.referencesVera, G., Daniel, V., La, P.D.E., Mensual, D., Con, D.E.E., Pronóstico de la demanda mensual de electricidad con series de tiempo (2016) Revista EIA, 13, p. 11
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem