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On the network topology of variance decompositions: measuring the connectedness of financial firms (Reprinted from Journal of Econometrics, Vol 182, Issue 1, September 2014, Pages 119-134)

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dc.contributor.coauthorDiebold, Francis X.
dc.contributor.departmentDepartment of Economics
dc.contributor.kuauthorYılmaz, Kamil
dc.contributor.otherDepartment of Economics
dc.contributor.schoolcollegeinstituteCollege of Administrative Sciences and Economics
dc.date.accessioned2024-12-29T09:41:09Z
dc.date.issued2023
dc.description.abstractWe propose several connectedness measures built from pieces of variance decomposi-tions, and we argue that they provide natural and insightful measures of connectedness. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately related to key measures of connectedness used in the network literature. Building on these insights, we track daily time-varying connectedness of major U.S. financial institutions' stock return volatilities in recent years, with emphasis on the financial crisis of 2007-2008.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.sponsorsIt is an honor to dedicate this paper to the memory of Halbert L. White, Jr. For helpful guidance we thank the editors (Xiaohong Chen and Norman Swanson) and several anonymous referees. We are also grateful for comments from seminar/conference participants at AEA, Bank of Chile, Bank of Norway, Bilkent, CFTC, Cornell, EC 2 , ECB, ESEM, Federal Reserve Banks of Cleveland, Kansas City and Philadelphia, Federal Reserve Board, Frankfurt, GW, Georgia Tech, IMF, Koc, Oxford, Penn, Princeton, Rice, Rutgers, SQA, and UCSD. Special thanks go to Yacine Ait-Sahalia, Celso Brunetti, David Easley, Blake LeBaron, Andrew Lo, Robert May, Mila Getmansky Sherman, Christopher Sims, and Norman Swanson. For financial support, Diebold thanks the US National Science Foundation and Yilmaz thanks the Turkish Scientific and Technological Research Council (TUBITAK) . The usual disclaimer applies.
dc.description.volume234
dc.identifier.doi10.1016/j.jeconom.2023.03.003
dc.identifier.eissn1872-6895
dc.identifier.issn0304-4076
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85149885827
dc.identifier.urihttps://doi.org/10.1016/j.jeconom.2023.03.003
dc.identifier.urihttps://hdl.handle.net/20.500.14288/23558
dc.identifier.wos1170855300011
dc.keywordsRisk measurement
dc.keywordsRisk management
dc.keywordsPortfolio allocation
dc.keywordsMarket risk
dc.keywordsCredit risk
dc.keywordsSystemic risk
dc.keywordsAsset markets
dc.keywordsDegree distribution
dc.languageen
dc.publisherElsevier Science Sa
dc.relation.grantnoUS National Science Foundation
dc.relation.grantnoTurkish Scientific and Technological Research Council (TUBITAK)
dc.sourceJournal of Econometrics
dc.subjectEconomics
dc.subjectMathematics
dc.subjectInterdisciplinary applications
dc.subjectSocial sciences
dc.subjectMathematical methods
dc.titleOn the network topology of variance decompositions: measuring the connectedness of financial firms (Reprinted from Journal of Econometrics, Vol 182, Issue 1, September 2014, Pages 119-134)
dc.typeOther
dc.type.otherReprint
dspace.entity.typePublication
local.contributor.kuauthorYılmaz, Kamil
relation.isOrgUnitOfPublication7ad2a3bb-d8d9-4cbd-a6a3-3ca4b30b40c3
relation.isOrgUnitOfPublication.latestForDiscovery7ad2a3bb-d8d9-4cbd-a6a3-3ca4b30b40c3

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