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On the network topology of variance decompositions: measuring the connectedness of financial firms

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dc.contributor.coauthorDiebold, Francis X.
dc.contributor.departmentDepartment of Economics
dc.contributor.kuauthorYılmaz, Kamil
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Economics
dc.contributor.schoolcollegeinstituteCollege of Administrative Sciences and Economics
dc.contributor.yokid6111
dc.date.accessioned2024-11-09T23:26:44Z
dc.date.issued2014
dc.description.abstractWe propose several connectedness measures built from pieces of variance decompositions, 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 US 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.issue1
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsorshipUS National Science Foundation
dc.description.sponsorshipTurkish Scientific and Technological Research Council (TUBITAK) It 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<SUP>2</SUP>, 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.volume182
dc.identifier.doi10.1016/j.jeconom.2014.04.012
dc.identifier.eissn1872-6895
dc.identifier.issn0304-4076
dc.identifier.scopus2-s2.0-84901841234
dc.identifier.urihttp://dx.doi.org/10.1016/j.jeconom.2014.04.012
dc.identifier.urihttps://hdl.handle.net/20.500.14288/11582
dc.identifier.wos337881300010
dc.keywordsRisk measurement
dc.keywordsRisk management
dc.keywordsPortfolio allocation
dc.keywordsMarket risk
dc.keywordsCredit risk
dc.keywordsSystemic risk
dc.keywordsAsset markets
dc.keywordsDegree distribution impulse-response analysis
dc.languageEnglish
dc.publisherElsevier Science Sa
dc.sourceJournal of Econometrics
dc.subjectEconomics
dc.subjectMathematics
dc.subjectBusiness, economics
dc.subjectSocial science
dc.titleOn the network topology of variance decompositions: measuring the connectedness of financial firms
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authorid0000-0003-2455-2099
local.contributor.kuauthorYılmaz, Kamil
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