DC FieldValueLanguage
dc.contributor.authorKallandranis, Christos-
dc.contributor.authorVlassas, Ioannis-
dc.contributor.authorDimitriou, Dimitrios-
dc.contributor.authorTsioutsios, Alexandros-
dc.contributor.authorDiakodimitriou, Danai-
dc.date.accessioned2024-03-04T23:37:21Z-
dc.date.available2024-03-04T23:37:21Z-
dc.date.issued2023-01-01-
dc.identifierscopus-85184699469-
dc.identifier.issn17563615-
dc.identifier.issn17563607-
dc.identifier.other85184699469-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/1375-
dc.description.abstractThis study examines empirically the volatility comovement between crude oil prices and key agricultural commodities for a series of shocks faced by the global econ-omy. Using both a multivariate Baba–Engle–Kraft–Kroner generalized autoregres-sive conditional heteroscedasticity (BEKK-GARCH) model to estimate the volatile comovements and detect possible contagion effects and a wavelet coherence analysis to test for time–frequency connectedness, we find positive correlation patterns between cocoa, corn and cotton prices and West Texas Intermediate oil price fluc-tuations. This correlation pattern is particularly evident in the global financial cri-sis, the eurozone sovereign debt crisis, the Covid-19 crisis and the Russo-Ukrainian War, which confirms the increased spillover during the shocks. These findings indi-cate a pattern of contagion for all assets, which could be attributed to their com-mon trade and financial characteristics, having important implications for portfolio managers, investors and government agencies. Hence, new policies are essential for safeguarding oil and agricultural commodities markets against future crises.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Energy Marketsen_US
dc.subjectAgriculture pricesen_US
dc.subjectCrude oilen_US
dc.subjectFinancial crisesen_US
dc.subjectMultivariate generalized autoregressive conditional heteroscedasticity (GARCH)en_US
dc.subjectWavelet coherence analysisen_US
dc.titleOn the contagion effect between crude oil and agricultural commodity markets: a dynamic conditional correlation and spectral analysisen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-85184699469-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Accounting and Financeen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume17en_US
dc.relation.issue3en_US
dc.identifier.spage1en_US
dc.identifier.epage14en_US
dc.linkhttps://ssrn.com/abstract=4706544en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsSubscriptionen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
item.openairetypeArticle-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptDepartment of Accounting and Finance-
crisitem.author.deptDepartment of Accounting and Finance-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0003-2111-4448-
crisitem.author.orcid0009-0007-9899-6828-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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