Can credit spreads help predict a yield curve?
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Abdymomunov, Azamat | - |
dc.contributor.author | Kang, Kyu Ho | - |
dc.contributor.author | Kim, Ki Jeong | - |
dc.date.accessioned | 2021-09-03T23:32:46Z | - |
dc.date.available | 2021-09-03T23:32:46Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016-06 | - |
dc.identifier.issn | 0261-5606 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/88575 | - |
dc.description.abstract | In 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.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.subject | GOVERNMENT BOND YIELDS | - |
dc.subject | TERM STRUCTURE MODELS | - |
dc.subject | AFFINE MODELS | - |
dc.subject | DETERMINANTS | - |
dc.subject | FORECASTS | - |
dc.subject | DENSITY | - |
dc.subject | US | - |
dc.title | Can credit spreads help predict a yield curve? | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Kyu Ho | - |
dc.identifier.doi | 10.1016/j.jimonfin.2016.02.003 | - |
dc.identifier.scopusid | 2-s2.0-84959473013 | - |
dc.identifier.wosid | 000374814400003 | - |
dc.identifier.bibliographicCitation | JOURNAL OF INTERNATIONAL MONEY AND FINANCE, v.64, pp.39 - 61 | - |
dc.relation.isPartOf | JOURNAL OF INTERNATIONAL MONEY AND FINANCE | - |
dc.citation.title | JOURNAL OF INTERNATIONAL MONEY AND FINANCE | - |
dc.citation.volume | 64 | - |
dc.citation.startPage | 39 | - |
dc.citation.endPage | 61 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalWebOfScienceCategory | Business, Finance | - |
dc.subject.keywordPlus | GOVERNMENT BOND YIELDS | - |
dc.subject.keywordPlus | TERM STRUCTURE MODELS | - |
dc.subject.keywordPlus | AFFINE MODELS | - |
dc.subject.keywordPlus | DETERMINANTS | - |
dc.subject.keywordPlus | FORECASTS | - |
dc.subject.keywordPlus | DENSITY | - |
dc.subject.keywordPlus | US | - |
dc.subject.keywordAuthor | Density prediction | - |
dc.subject.keywordAuthor | Dynamic Nelson-Siegel | - |
dc.subject.keywordAuthor | Predictive likelihood | - |
dc.subject.keywordAuthor | Bayesian MCMC estimation | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.