Tail Risk Connectedness Between US Industries

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dc.cclicenceCC-BYen
dc.contributor.authorNguyen, Linh H.
dc.contributor.authorNguyen, Linh Xuan Diep
dc.contributor.authorTan, Linzhi
dc.date.acceptance2020-06-18
dc.date.accessioned2020-07-21T10:44:10Z
dc.date.available2020-07-21T10:44:10Z
dc.date.issued2020-07-15
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractWe use the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression technique to construct and analyse the complete tail risk connectedness network of the whole US industry system. We also investigate the empirical relationship between input-output linkages and the tail risk spillovers among US industries. Our findings identify the tail-risk drivers, tail-risk receivers, and tail-risk distributors among industries and confirm that the actual trade flow between industries is a major driver of their tail risk connectedness.en
dc.funderNo external funderen
dc.identifier.citationNguyen, L.H., Nguyen, L.X.D., Tan, L. (2020) Tail risk connectedness between US industries. International Journal of Finance and Economics.en
dc.identifier.doihttps://doi.org/10.1002/ijfe.1979
dc.identifier.issn1076-9307
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/20005
dc.language.isoenen
dc.peerreviewedYesen
dc.publisherWileyen
dc.researchinstituteFinance and Banking Research Group (FiBRe)en
dc.subjectBusiness Linkageen
dc.subjectInput-outputen
dc.subjectQuantile regressionen
dc.subjectTail risk networken
dc.subjectTail risk spilloveren
dc.titleTail Risk Connectedness Between US Industriesen
dc.typeArticleen

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