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Can credit spreads help predict a yield curve?

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dc.contributor.authorAbdymomunov, Azamat-
dc.contributor.authorKang, Kyu Ho-
dc.contributor.authorKim, Ki Jeong-
dc.date.accessioned2021-09-03T23:32:46Z-
dc.date.available2021-09-03T23:32:46Z-
dc.date.created2021-06-18-
dc.date.issued2016-06-
dc.identifier.issn0261-5606-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/88575-
dc.description.abstractIn this paper we investigate whether information in credit spreads helps improve the forecasts of government bond yields. To do this, we propose and estimate a joint dynamic Nelson-Siegel (DNS) model of the U.S. Treasury yield curve and the credit spread curve. The model accounts for the possibility of regime changes in yield curve dynamics and incorporates a zero lower bound constraint on yields. We show that our joint model produces more accurate out-of sample density forecasts of bond yields than does the yield-only DNS model. In addition, we demonstrate that incorporating regime changes and a zero lower bound constraint is essential for forecast improvements. (C) 2016 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectGOVERNMENT BOND YIELDS-
dc.subjectTERM STRUCTURE MODELS-
dc.subjectAFFINE MODELS-
dc.subjectDETERMINANTS-
dc.subjectFORECASTS-
dc.subjectDENSITY-
dc.subjectUS-
dc.titleCan credit spreads help predict a yield curve?-
dc.typeArticle-
dc.contributor.affiliatedAuthorKang, Kyu Ho-
dc.identifier.doi10.1016/j.jimonfin.2016.02.003-
dc.identifier.scopusid2-s2.0-84959473013-
dc.identifier.wosid000374814400003-
dc.identifier.bibliographicCitationJOURNAL OF INTERNATIONAL MONEY AND FINANCE, v.64, pp.39 - 61-
dc.relation.isPartOfJOURNAL OF INTERNATIONAL MONEY AND FINANCE-
dc.citation.titleJOURNAL OF INTERNATIONAL MONEY AND FINANCE-
dc.citation.volume64-
dc.citation.startPage39-
dc.citation.endPage61-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalWebOfScienceCategoryBusiness, Finance-
dc.subject.keywordPlusGOVERNMENT BOND YIELDS-
dc.subject.keywordPlusTERM STRUCTURE MODELS-
dc.subject.keywordPlusAFFINE MODELS-
dc.subject.keywordPlusDETERMINANTS-
dc.subject.keywordPlusFORECASTS-
dc.subject.keywordPlusDENSITY-
dc.subject.keywordPlusUS-
dc.subject.keywordAuthorDensity prediction-
dc.subject.keywordAuthorDynamic Nelson-Siegel-
dc.subject.keywordAuthorPredictive likelihood-
dc.subject.keywordAuthorBayesian MCMC estimation-
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