{"title":"Forecasting corporate bond returns amid climate change risk: A dynamic forecast combination approach","authors":"Feng Ma, Yangli Guo, Qin Luo, Juandan Zhong","doi":"10.1016/j.jimonfin.2025.103324","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines the predictability of Chinese corporate bond returns in the context of climate change risk using the Climate Change Concern Index (CCCI) derived from text data. The results show that the CCCI has strong predictive power in both the in-sample and out-of-sample analyses, especially for AAA-rated bonds and bonds with shorter maturities. In addition, applying the Dynamic Forecast Combination method shows that state factors such as economic activity significantly improve the overall predictive power of bond returns, especially in times of low economic activity. The inclusion of climate risk in the prediction of bond returns also brings tangible economic benefits, as shown by the increased certainty-equivalent returns and Sharpe ratios. These results show that climate risk is a significant source of systemic risk and can predict risk premiums in the bond market. Investors should also consider climate risk and economic conditions when constructing portfolios.</div></div>","PeriodicalId":48331,"journal":{"name":"Journal of International Money and Finance","volume":"154 ","pages":"Article 103324"},"PeriodicalIF":2.8000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of International Money and Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0261560625000592","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study examines the predictability of Chinese corporate bond returns in the context of climate change risk using the Climate Change Concern Index (CCCI) derived from text data. The results show that the CCCI has strong predictive power in both the in-sample and out-of-sample analyses, especially for AAA-rated bonds and bonds with shorter maturities. In addition, applying the Dynamic Forecast Combination method shows that state factors such as economic activity significantly improve the overall predictive power of bond returns, especially in times of low economic activity. The inclusion of climate risk in the prediction of bond returns also brings tangible economic benefits, as shown by the increased certainty-equivalent returns and Sharpe ratios. These results show that climate risk is a significant source of systemic risk and can predict risk premiums in the bond market. Investors should also consider climate risk and economic conditions when constructing portfolios.
期刊介绍:
Since its launch in 1982, Journal of International Money and Finance has built up a solid reputation as a high quality scholarly journal devoted to theoretical and empirical research in the fields of international monetary economics, international finance, and the rapidly developing overlap area between the two. Researchers in these areas, and financial market professionals too, pay attention to the articles that the journal publishes. Authors published in the journal are in the forefront of scholarly research on exchange rate behaviour, foreign exchange options, international capital markets, international monetary and fiscal policy, international transmission and related questions.