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dc.contributor.authorBoeckelmann, Lukas
hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorStalla-Bourdillon, Arthur
dc.date.accessioned2021-09-08T12:21:36Z
dc.date.available2021-09-08T12:21:36Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/21747
dc.description.abstractfrNous proposons une nouvelle méthodologie pour estimer les contagions financières à l’aided’une version structurelle de l’approche de Diebold-Yilmaz. Le cœur de notre approche repose sur un modèle SVAR-GARCH qui est identifié par hétéroscédasticité et par la contribution maximale des chocs, et qui permet d’obtenir des décompositions non-constantes de la variance des erreurs de prévision. Nous analysons les contagions entre les CDS souverains et bancaires de la Zone Euro. En termes de méthodologie, nous trouvons que notre modèle permet de mieux identifier les chocs par rapport aux autres approches de la littérature, et qu’il est aussi plus réactif que les modèles estimés sur fenêtres glissantes. Nous trouvons, en moyenne, que la contagion explique 37% de la variation des séries de notre échantillon, avec toutefois de fortes variations dans le temps.en
dc.language.isoenen
dc.subjectCredit default swapen
dc.subjectsovereign debten
dc.subjectsystemic risken
dc.subjectStructural vector autoregressiveen
dc.subjectidentification by heteroskedasticityen
dc.subjectcontagionen
dc.subjectdette souveraineen
dc.subjectrisque systémiqueen
dc.subject.ddc658.1en
dc.subject.classificationjelC.C5.C59en
dc.subject.classificationjelG.G1.G18en
dc.subject.classificationjelG.G2.G21en
dc.titleStructural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmissionen
dc.typeDocument de travail / Working paper
dc.description.abstractenWe propose a novel approach to quantify spillovers on financial markets based on a structural version of the Diebold-Yilmaz framework. Key to our approach is a SVAR-GARCH model that is statistically identified by heteroskedasticity, economically identifiedby maximum shock contribution and that allows for time-varying forecast error variance decompositions. We analyze credit risk spillovers between EZ sovereign and bank CDS. Methodologically, we find the model to better match economic narratives compared with common spillover approaches and to be more reactive than models relying on rolling window estimations. We find, on average, spillovers to explain 37% of the variation in our sample, amid a strong variation of the latter over time.en
dc.publisher.cityParisen
dc.identifier.citationpages61en
dc.relation.ispartofseriestitleDocuments de Travail de la Banque de Franceen
dc.relation.ispartofseriesnumberWP 798en
dc.relation.isversionofbkurlhttps://publications.banque-france.fr/en/structural-estimation-time-varying-spillovers-application-international-credit-risk-transmissionen
dc.identifier.urlsitehttps://publications.banque-france.fr/sites/default/files/medias/documents/wp798.pdfen
dc.subject.ddclabelGestion financière, capital risque, création de valeuren
dc.identifier.citationdate2021-05
dc.description.ssrncandidatenon
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2021-09-08T12:06:46Z
hal.identifierhal-03338209
hal.version1
dc.subject.classificationjelHALC - Mathematical and Quantitative Methods::C5 - Econometric Modeling::C59 - Otheren
dc.subject.classificationjelHALG - Financial Economics::G1 - General Financial Markets::G18 - Government Policy and Regulationen
dc.subject.classificationjelHALG - Financial Economics::G2 - Financial Institutions and Services::G21 - Banks; Depository Institutions; Micro Finance Institutions; Mortgagesen
hal.date.transferred2021-09-08T12:21:37Z
hal.author.functionaut
hal.author.functionaut


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