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dc.creatorMonge, M. (Manuel)-
dc.creatorGil-Alana, L.A. (Luis A.)-
dc.date.accessioned2023-11-21T13:39:36Z-
dc.date.available2023-11-21T13:39:36Z-
dc.date.issued2020-
dc.identifier.citationMonge, M. (Manuel); Gil-Alana, L.A. (Luis A.). "The lithium industry and analysis of the beta term structure of oil companies". Risks. 8 (4), 2020, 130es
dc.identifier.issn2227-9091-
dc.identifier.urihttps://hdl.handle.net/10171/67934-
dc.description.abstractAccording to a statement made in the BP Energy Outlook report in 2017, most of the world’s liquid fuel (petroleum) is being consumed by the transportation industry. The mechanisms used to stimulate changes in the energy markets are affected by government policies that act in more ambitious ways than purely market-driven forces; different governments have promoted incentives involving electric mobility, especially in urban areas. The substitution for crude oil by renewable energy inputs in the transport sector is a major concern for oil producers. Among the different types of clean energies, lithium (Li) is currently assuming an increasingly strategic role. The goals of this paper are two-fold: First, we study the dynamics of the lithium industry and then the beta risk behavior of the 10 largest oil companies in the world for the time period between 11 February 2008 and 10 January 2019. We use an approach based on the continuous wavelet transform (CWT) method. The results indicate that there is a period of dependence between late 2013 and 2016 that occurs in the long-run frequencies of between 32 and 198 days for all cases, except for in the case of PetroChina, thereby demonstrating that the beta term is time-varying. We also find evidence that the beta term reflects and advances oil companies’ responsiveness to movements in the lithium market. In the second part of the paper, we study the dynamics of the beta series by using long-run dependence approaches. The results indicate that the betas are highly persistent, with the order of integration found to be significantly above 1 in all cases.es_ES
dc.description.sponsorshipLuis A. Gil-Alana gratefully acknowledges financial support from the Ministerio de Economía y Competitividad (ECO2017-85503-R). Luis A. Gil-Alana and Manuel Monge also acknowledge support from an internal Project from the Universidad Francisco de Vitoria. Comments from the editor and five anonymous reviewers are gratefully acknowledged.es_ES
dc.language.isoenges_ES
dc.publisherMDPI AGes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ECO2017-85503-R/ES/INTEGRACION FRACCIONAL, PROCESOS DE MEMORIA LARGA Y NO LINEALIDADES EN SERIES DE TIEMPO. EVIDENCIA EN LOS PAISES EN VIAS DE DESARROLLOes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectLithium industryes_ES
dc.subjectBetases_ES
dc.subjectDependencees_ES
dc.subjectWaveletses_ES
dc.subjectFractional integrationes_ES
dc.titleThe lithium industry and analysis of the beta term structure of oil companieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.noteThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.identifier.doi10.3390/risks8040130-
dadun.citation.number4es_ES
dadun.citation.publicationNameRiskses_ES
dadun.citation.startingPage130es_ES
dadun.citation.volume8es_ES

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