Energy markets e Who are the influencers?
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/33091 https://doi.org/10.1016/j.energy.2021.121962 |
Resumo: | The energy markets have recently undergone important transformations (e.g. deregulation, technological progress, renewable energy deployment and changing energy consumer behaviour) and witnessed a variety of crisis periods, affecting the relationships among energy commodities and their interactions with clean energy indices. This has implications for price discovery, asset allocation and risk management, which requires in-depth analysis to uncover and identify which energy indices (or forms of energy) lead others or are the most influential, while accounting for asymmetry and non-linearity characteristics. To uncover the complex structure of the relationship across the returns of seven different energy commodities and two clean energy stock indices, we apply Granger causality and transfer entropy in both static and dynamic approaches. The results from the Granger causality analysis identify the influence of the other energy products on natural gas, whereas the transfer entropy analysis reveals the importance of WTI oil and the influence of clean energy indices. Diesel is the most influenced energy commodity. A rolling windows analysis confirms those findings and shows evidence of a time-variation that reflects the impacts of crisis periods, especially the pandemic, on the dynamics of relationships |
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Energy markets e Who are the influencers?energy marketsClean and dirty energy assetsgranger causalitytranser entropyinfluencerThe energy markets have recently undergone important transformations (e.g. deregulation, technological progress, renewable energy deployment and changing energy consumer behaviour) and witnessed a variety of crisis periods, affecting the relationships among energy commodities and their interactions with clean energy indices. This has implications for price discovery, asset allocation and risk management, which requires in-depth analysis to uncover and identify which energy indices (or forms of energy) lead others or are the most influential, while accounting for asymmetry and non-linearity characteristics. To uncover the complex structure of the relationship across the returns of seven different energy commodities and two clean energy stock indices, we apply Granger causality and transfer entropy in both static and dynamic approaches. The results from the Granger causality analysis identify the influence of the other energy products on natural gas, whereas the transfer entropy analysis reveals the importance of WTI oil and the influence of clean energy indices. Diesel is the most influenced energy commodity. A rolling windows analysis confirms those findings and shows evidence of a time-variation that reflects the impacts of crisis periods, especially the pandemic, on the dynamics of relationships2023-01-03T15:58:47Z2023-01-032022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/33091http://hdl.handle.net/10174/33091https://doi.org/10.1016/j.energy.2021.121962porFerreira, P.; Almeida, D.; Dionísio, A.; Bouri, E.; Quintino, D. (2022). “Energy markets – who are the influencers?” Energy, 239, Part A, 15.pjsf@uevora.ptandreia@uevora.ptdora.almeida@uevora.ptndnd748Ferreira, PauloDionisio, AndreiaAlmeida, DoraBouri, ElieQintino, Derickinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:33:56Zoai:dspace.uevora.pt:10174/33091Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:21:47.079854Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Energy markets e Who are the influencers? |
title |
Energy markets e Who are the influencers? |
spellingShingle |
Energy markets e Who are the influencers? Ferreira, Paulo energy markets Clean and dirty energy assets granger causality transer entropy influencer |
title_short |
Energy markets e Who are the influencers? |
title_full |
Energy markets e Who are the influencers? |
title_fullStr |
Energy markets e Who are the influencers? |
title_full_unstemmed |
Energy markets e Who are the influencers? |
title_sort |
Energy markets e Who are the influencers? |
author |
Ferreira, Paulo |
author_facet |
Ferreira, Paulo Dionisio, Andreia Almeida, Dora Bouri, Elie Qintino, Derick |
author_role |
author |
author2 |
Dionisio, Andreia Almeida, Dora Bouri, Elie Qintino, Derick |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Ferreira, Paulo Dionisio, Andreia Almeida, Dora Bouri, Elie Qintino, Derick |
dc.subject.por.fl_str_mv |
energy markets Clean and dirty energy assets granger causality transer entropy influencer |
topic |
energy markets Clean and dirty energy assets granger causality transer entropy influencer |
description |
The energy markets have recently undergone important transformations (e.g. deregulation, technological progress, renewable energy deployment and changing energy consumer behaviour) and witnessed a variety of crisis periods, affecting the relationships among energy commodities and their interactions with clean energy indices. This has implications for price discovery, asset allocation and risk management, which requires in-depth analysis to uncover and identify which energy indices (or forms of energy) lead others or are the most influential, while accounting for asymmetry and non-linearity characteristics. To uncover the complex structure of the relationship across the returns of seven different energy commodities and two clean energy stock indices, we apply Granger causality and transfer entropy in both static and dynamic approaches. The results from the Granger causality analysis identify the influence of the other energy products on natural gas, whereas the transfer entropy analysis reveals the importance of WTI oil and the influence of clean energy indices. Diesel is the most influenced energy commodity. A rolling windows analysis confirms those findings and shows evidence of a time-variation that reflects the impacts of crisis periods, especially the pandemic, on the dynamics of relationships |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01T00:00:00Z 2023-01-03T15:58:47Z 2023-01-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/33091 http://hdl.handle.net/10174/33091 https://doi.org/10.1016/j.energy.2021.121962 |
url |
http://hdl.handle.net/10174/33091 https://doi.org/10.1016/j.energy.2021.121962 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Ferreira, P.; Almeida, D.; Dionísio, A.; Bouri, E.; Quintino, D. (2022). “Energy markets – who are the influencers?” Energy, 239, Part A, 15. pjsf@uevora.pt andreia@uevora.pt dora.almeida@uevora.pt nd nd 748 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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