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.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
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-
Appears in Collections:Articles / Άρθρα
CORE Recommender
Show simple item record

Page view(s)

29
checked on Nov 5, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.