Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022

ilustraciones, diagramas

Autores:: Marín-Rodríguez, Nini Johana

Tipo de recurso:: Doctoral thesis

Fecha de publicación:: 2023

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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repository_id_str
dc.title.eng.fl_str_mv	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
dc.title.translated.spa.fl_str_mv	Análisis del co-movimiento dinámico de los precios del petróleo, los bonos verdes y las emisiones de CO2, 2014-2022
title	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
spellingShingle	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022 620 - Ingeniería y operaciones afines 330 - Economía::333 - Economía de la tierra y de la energía Petróleo - Aspectos económicos Petroleum CO2 emissions Co-movements Dependence Oil prices Green bonds Scientometric analysis Energy markets Machine learning Emisiones de CO2 Co-movimientos Dependencia Precios del petróleo Bonos verdes Análisis cienciométrico
title_short	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
title_full	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
title_fullStr	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
title_full_unstemmed	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
title_sort	Dynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022
dc.creator.fl_str_mv	Marín-Rodríguez, Nini Johana
dc.contributor.advisor.none.fl_str_mv	Botero Botero, Sergio González Ruiz, Juan David
dc.contributor.author.none.fl_str_mv	Marín-Rodríguez, Nini Johana
dc.contributor.researchgroup.spa.fl_str_mv	Modelamiento y Análisis Energía Ambiente Economía
dc.contributor.orcid.spa.fl_str_mv	Marín-Rodríguez, Nini Johana [0000-0003-4318-7947] González Ruiz, Juan David [0000-0003-4425-7687]
dc.contributor.cvlac.spa.fl_str_mv	Marín-Rodríguez, Nini Johana [0001337439]
dc.contributor.scopus.spa.fl_str_mv	Marín-Rodríguez, Nini Johana [57195913643]
dc.contributor.researchgate.spa.fl_str_mv	Marín-Rodríguez, Nini Johana [ J-4437-2015]
dc.contributor.googlescholar.spa.fl_str_mv	Marín-Rodríguez, Nini Johana [https://scholar.google.com/citations?user=QnylAiQAAAAJ&hl=es]
dc.subject.ddc.spa.fl_str_mv	620 - Ingeniería y operaciones afines 330 - Economía::333 - Economía de la tierra y de la energía
topic	620 - Ingeniería y operaciones afines 330 - Economía::333 - Economía de la tierra y de la energía Petróleo - Aspectos económicos Petroleum CO2 emissions Co-movements Dependence Oil prices Green bonds Scientometric analysis Energy markets Machine learning Emisiones de CO2 Co-movimientos Dependencia Precios del petróleo Bonos verdes Análisis cienciométrico
dc.subject.lemb.spa.fl_str_mv	Petróleo - Aspectos económicos
dc.subject.lemb.eng.fl_str_mv	Petroleum
dc.subject.proposal.eng.fl_str_mv	CO2 emissions Co-movements Dependence Oil prices Green bonds Scientometric analysis Energy markets Machine learning
dc.subject.proposal.spa.fl_str_mv	Emisiones de CO2 Co-movimientos Dependencia Precios del petróleo Bonos verdes Análisis cienciométrico
description	ilustraciones, diagramas
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-05-30T12:47:08Z
dc.date.available.none.fl_str_mv	2023-05-30T12:47:08Z
dc.date.issued.none.fl_str_mv	2023-05-29
dc.type.spa.fl_str_mv	Trabajo de grado - Doctorado
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/doctoralThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv	http://purl.org/coar/resource_type/c_db06
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TD
format	http://purl.org/coar/resource_type/c_db06
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/83906
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/83906 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	eng
language	eng
dc.relation.indexed.spa.fl_str_mv	RedCol LaReferencia
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
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dc.publisher.faculty.spa.fl_str_mv	Facultad de Minas
dc.publisher.place.spa.fl_str_mv	Medellín, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Medellín
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Botero Botero, Sergio8570007158169aa7e9d0ec814380de02González Ruiz, Juan Davide44383d10b9ef44cc877f20dcbd6e649500Marín-Rodríguez, Nini Johana77516f2171852ca338950d4ac0c7c1c4500Modelamiento y Análisis Energía Ambiente EconomíaMarín-Rodríguez, Nini Johana [0000-0003-4318-7947]González Ruiz, Juan David [0000-0003-4425-7687]Marín-Rodríguez, Nini Johana [0001337439]Marín-Rodríguez, Nini Johana [57195913643]Marín-Rodríguez, Nini Johana [ J-4437-2015]Marín-Rodríguez, Nini Johana [https://scholar.google.com/citations?user=QnylAiQAAAAJ&hl=es]2023-05-30T12:47:08Z2023-05-30T12:47:08Z2023-05-29https://repositorio.unal.edu.co/handle/unal/83906Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasThis research addresses the problem of the coverage gap in the extant literature to know how oil prices, green bonds, and CO2 emissions are related to each other. Additionally, to research the short and long-term relations using a machine learning model for measuring co-movements among these important variables in the global energy transition context. Therefore, this study’s primary objective is to analyze the results of the short- and long-term co-movements and the implications for researchers, investors, and policy-makers. To validate the analysis, we use daily data from oil prices, green bonds, and CO2 emissions from 2014 to 2022. In addition, a scientometric analysis of the principal methodologies for measuring the co-movements among financial markets, using techniques such as the analysis of (i) sources, (ii) authors, (iii) documents, and (iv) cluster analysis. In this way, this research applies methodologies like Granger Causality Test, Dynamic Conditional Correlation (DCC-Garch), Wavelet power spectrum (WPS), and wavelet coherence analyses (WCA). Additionally, this study employs a machine learning model for measuring the relationships among the selected variables. Specifically, the Fuzzy Logistic Autoencoder (FLAE) was implemented. Furthermore, the results of the machine learning model were validated and compared with the estimated models. Finally, this study represents a breakthrough in explaining the relationship among these variables.Esta investigación aborda el vacío en la literatura existente sobre cómo se relacionan entre sí los precios del petróleo, los bonos verdes y las emisiones de CO2. Además, se investigan las relaciones a corto y largo plazo de los co-movimientos entre estas importantes variables en el contexto de la transición energética mundial, utilizando un modelo de aprendizaje automático. Por lo tanto, el objetivo principal de este estudio es analizar los resultados de los co-movimientos a corto y largo plazo y las implicaciones para investigadores, inversores y responsables de política. Para validar el análisis, utilizamos datos diarios de los precios del petróleo, los bonos verdes y las emisiones de CO2 desde 2014 hasta 2022. Además, se realiza un análisis cienciométrico de las principales metodologías para medir los co-movimientos entre los mercados financieros, utilizando técnicas como el análisis de (i) fuentes, (ii) autores, (iii) documentos, y (iv) análisis de clusters. De este modo, esta investigación aplica metodologías como la prueba de causalidad de Granger, la correlación condicional dinámica (Dynamic Conditional Correlation, DCC-Garch), el espectro de potencia wavelet (Wavelet Power Spectrum, WPS) y el análisis de coherencia wavelet (Wavelet Coherence Analyses, WCA). Además, este estudio emplea un modelo de aprendizaje automático para medir las relaciones entre las variables seleccionadas. En concreto, se implementó el autoencoder logístico difuso (Fuzzy Logistic Autoencoder, FLAE). Además, los resultados del modelo de aprendizaje automático se validaron y compararon con los modelos estimados. Por último, este estudio representa un avance en la explicación de la relación entre estas variables. (Texto tomado de la fuente)DoctoradoDoctor en IngenieríaInvestigación en Finanzas (Finance Research)Área Curricular de Materiales y Nanotecnologíaxx, 225 páginasapplication/pdfengUniversidad Nacional de ColombiaMedellín - Minas - Doctorado en Ingeniería - Industria y OrganizacionesFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín620 - Ingeniería y operaciones afines330 - Economía::333 - Economía de la tierra y de la energíaPetróleo - Aspectos económicosPetroleumCO2 emissionsCo-movementsDependenceOil pricesGreen bondsScientometric analysisEnergy marketsMachine learningEmisiones de CO2Co-movimientosDependenciaPrecios del petróleoBonos verdesAnálisis cienciométricoDynamic co-movement analysis among oil prices, green bonds, and CO2 emissions, 2014-2022Análisis del co-movimiento dinámico de los precios del petróleo, los bonos verdes y las emisiones de CO2, 2014-2022Trabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDRedColLaReferenciaAbdelmaksoud, A. 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International Journal of Energy Sector Management, 12(4), 641–655. https://doi.org/10.1108/IJESM-10-2017-0013InvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83906/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL43209431.2023.pdf43209431.2023.pdfTesis de Doctorado en Ingeniería - Industria y Organizacionesapplication/pdf6943063https://repositorio.unal.edu.co/bitstream/unal/83906/2/43209431.2023.pdf128473cd57a75da98844e4453f66db86MD52THUMBNAIL43209431.2023.pdf.jpg43209431.2023.pdf.jpgGenerated Thumbnailimage/jpeg4698https://repositorio.unal.edu.co/bitstream/unal/83906/3/43209431.2023.pdf.jpg5fa86bee49a7de35247d40d4aa5c7e4fMD53unal/83906oai:repositorio.unal.edu.co:unal/839062023-08-07 23:03:40.453Repositorio Institucional Universidad Nacional de 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