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News sentiment and bond risk premia

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dc.contributor.authorKang, Chang-Mo-
dc.contributor.authorKim, Donghyun-
dc.contributor.authorPark, Hoyoung-
dc.date.accessioned2026-05-05T09:34:49Z-
dc.date.available2026-05-05T09:34:49Z-
dc.date.issued2026-12-
dc.identifier.issn2332-2039-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212499-
dc.description.abstractThis study examines whether and how news sentiment regarding interest rate changes predicts bond risk premia in Korea, a leading emerging market. Using machine learning techniques, we construct the Bond News Sentiment Index (BNSI) from news articles on interest rates. Our analysis reveals that the BNSI has a hump-shaped relationship with bond risk premia in the following month. This result suggests that a stronger consensus of news articles on interest rate changes signals decreases in uncertainty, leading to lower bond risk premia. We propose a BNSI-based forecasting factor, which exhibits predictive power beyond existing factors both in- and out-of-sample-
dc.format.extent15-
dc.language영어-
dc.language.isoENG-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titleNews sentiment and bond risk premia-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1080/23322039.2025.2602340-
dc.identifier.scopusid2-s2.0-105025413973-
dc.identifier.wosid001645517400001-
dc.identifier.bibliographicCitationCOGENT ECONOMICS & FINANCE, v.14, no.1, pp 1 - 15-
dc.citation.titleCOGENT ECONOMICS & FINANCE-
dc.citation.volume14-
dc.citation.number1-
dc.citation.startPage1-
dc.citation.endPage15-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClassesci-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalWebOfScienceCategoryEconomics-
dc.subject.keywordPlusINVESTOR SENTIMENT-
dc.subject.keywordPlusSTOCK RETURNS-
dc.subject.keywordPlusUNCERTAINTY-
dc.subject.keywordPlusPOLICY-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusLIQUIDITY-
dc.subject.keywordPlusMATURITY-
dc.subject.keywordAuthorNews sentiment-
dc.subject.keywordAuthorbond risk premia-
dc.subject.keywordAuthorinterest rates-
dc.subject.keywordAuthorfactor analysis-
dc.subject.keywordAuthormachine learning-
dc.subject.keywordAuthorword-to-vector-
dc.identifier.urlhttps://www.tandfonline.com/doi/full/10.1080/23322039.2025.2602340-
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서울 경영대학 > 서울 파이낸스경영학과 > 1. Journal Articles

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