News sentiment and bond risk premiaopen access
- Authors
- Kang, Chang-Mo; Kim, Donghyun; Park, 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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