{"title":"The impact of carbon transition risk concerns on stock market cycles: Evidence from China","authors":"Qin Luo , Xinjie Lu , Dengshi Huang , Qing Zeng","doi":"10.1016/j.techfore.2024.123827","DOIUrl":null,"url":null,"abstract":"<div><div>This study constructs a measure of the Carbon Transition Risk Concern (CTRC) index using a textual method. Then, the paper investigates the ability of the CTRC to influence stock market cycles (volatility) in China. The out-of-sample results indicate that the CTRC significantly increases the predictive accuracy. More importantly, the CTRC contains unique information, even considering the macroeconomic variables and economic policy uncertainty. The channel analysis also suggests that the CTRC primarily affects the stock market cycles through the discount rate channel rather than the cash flow channel. Overall, this study uncovers the predictive capability of the CTRC for stock market volatility in China, offering a fresh perspective for investors and policymakers to enhance their understanding of stock market cycles.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123827"},"PeriodicalIF":12.9000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040162524006255","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
This study constructs a measure of the Carbon Transition Risk Concern (CTRC) index using a textual method. Then, the paper investigates the ability of the CTRC to influence stock market cycles (volatility) in China. The out-of-sample results indicate that the CTRC significantly increases the predictive accuracy. More importantly, the CTRC contains unique information, even considering the macroeconomic variables and economic policy uncertainty. The channel analysis also suggests that the CTRC primarily affects the stock market cycles through the discount rate channel rather than the cash flow channel. Overall, this study uncovers the predictive capability of the CTRC for stock market volatility in China, offering a fresh perspective for investors and policymakers to enhance their understanding of stock market cycles.
期刊介绍:
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