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dc.contributor.authorAbdollahi, Hooman
dc.contributor.authorJunttila, Juha-Pekka
dc.contributor.authorLehkonen, Heikki
dc.date.accessioned2024-09-12T07:46:46Z
dc.date.available2024-09-12T07:46:46Z
dc.date.issued2024-05-13
dc.description.abstractTo assess similarities in international asset markets’ responses to political news, we construct a political news index using advanced natural language processing. We then examine how the volatility across international asset markets is connected to the development of our political news index by measuring the daily directional connectedness using a VAR-based framework. Finally, we apply an unsupervised algorithm to cluster markets based on their volatility connectedness to political news. Our analysis reveals eight distinct clusters that reflect the markets’ sensitivities to political dynamics. This data-driven analysis offers insights into the influence of political developments on market volatility.en_US
dc.identifier.citationAbdollahi H, Junttila, Lehkonen. Clustering asset markets based on volatility connectedness to political news. Journal of international financial markets, institutions, and money. 2024;93en_US
dc.identifier.cristinIDFRIDAID 2269389
dc.identifier.doi10.1016/j.intfin.2024.102004
dc.identifier.issn1042-4431
dc.identifier.issn1873-0612
dc.identifier.urihttps://hdl.handle.net/10037/34694
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalJournal of international financial markets, institutions, and money
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleClustering asset markets based on volatility connectedness to political newsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)