Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory

dc.contributor.author	Matyjaszek, Marta Janyna
dc.contributor.author	Riesgo Fernández, Pedro
dc.contributor.author	Krzemien, A.
dc.contributor.author	Wodarski, K.
dc.contributor.author	Fidalgo Valverde, Gregorio
dc.date.accessioned	2019-08-21T07:34:28Z
dc.date.available	2019-08-21T07:34:28Z
dc.date.issued	2019
dc.identifier.citation	Resources Policy, 61, p. 283-292 (2019); doi:10.1016/j.resourpol.2019.02.017
dc.identifier.issn	0301-4207
dc.identifier.uri	http://hdl.handle.net/10651/52383
dc.description.sponsorship	The first author greatly appreciates support from the Doctoral Research Fellowship of the “Luis Fernández Velasco” Foundation on Mineral & Mining Economics at the School of Mining, Energy and Material Engineering at the University of Oviedo (Spain).
dc.format.extent	p. 283-292
dc.language.iso	eng
dc.relation.ispartof	Resources Policy, 61
dc.rights	© 2019 Elsevier
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063026286&doi=10.1016%2fj.resourpol.2019.02.017&partnerID=40&md5=3bdb53e2b922ca4106ff0998ac7598b9
dc.title	Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory
dc.type	journal article
dc.identifier.doi	10.1016/j.resourpol.2019.02.017
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.resourpol.2019.02.017

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