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dc.creatorBillio, Monica
dc.creatorCaporin, Massimiliano
dc.creatorFrattarolo, Lorenzo
dc.creatorPelizzon, Loriana
dc.date.accessioned2021-09-28T09:35:08Z
dc.date.available2021-09-28T09:35:08Z
dc.date.issued2018-08-01
dc.identifier.urihttps://fif.hebis.de/xmlui/handle/123456789/2327
dc.description.abstractWe propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic normality of the quasi-maximum-likelihood estimator. We show how to isolate risk channels and we discuss how to compute target exposure able to reduce system variance. An empirical analysis on Euro-area cross-country holdings shows that Italy and Ireland are key players in spreading risk, France and Portugal are the major risk receivers, and we uncover Spain's non-trivial role as risk middleman.
dc.rightsAttribution-ShareAlike 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subjectFinancial Institutions
dc.subjectSystemic Risk Lab
dc.titleNetworks in Risk Spillovers: A Multivariate GARCH Perspective
dc.typeWorking Paper
dcterms.referenceshttps://fif.hebis.de/xmlui/handle/123456789/1352?BIC
dcterms.referenceshttps://fif.hebis.de/xmlui/handle/123456789/1397?Eikon
dc.source.filename225_SSRN-id3239369
dc.identifier.safeno225
dc.subject.keywordsspatial garch
dc.subject.keywordsnetwork
dc.subject.keywordsrisk spillover
dc.subject.keywordsfinancial spillover
dc.subject.jelC58
dc.subject.jelG10
dc.subject.topic1numericalConstrained
dc.subject.topic1miroslav
dc.subject.topic1network
dc.subject.topic2fiveYear
dc.subject.topic2itamar
dc.subject.topic2daily
dc.subject.topic3paper
dc.subject.topic3table
dc.subject.topic3normality
dc.subject.topic1nameConsumption
dc.subject.topic2nameFinancial Markets
dc.subject.topic3nameSystematic Risk
dc.identifier.doi10.2139/ssrn.3239369


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