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News sentiment and bond risk premiaopen access

Authors
Kang, Chang-MoKim, DonghyunPark, Hoyoung
Issue Date
Dec-2026
Publisher
TAYLOR & FRANCIS LTD
Keywords
News sentiment; bond risk premia; interest rates; factor analysis; machine learning; word-to-vector
Citation
COGENT ECONOMICS & FINANCE, v.14, no.1, pp 1 - 15
Pages
15
Indexed
SCOPUS
ESCI
Journal Title
COGENT ECONOMICS & FINANCE
Volume
14
Number
1
Start Page
1
End Page
15
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212499
DOI
10.1080/23322039.2025.2602340
ISSN
2332-2039
Abstract
This 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
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서울 경영대학 > 서울 파이낸스경영학과 > 1. Journal Articles

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