 Can energy predict the regional prices of carbon emission allowances in China?Li-Yang Guo, Chao Feng and Jun Yang International Review of Financial Analysis, 2022, vol. 82, issue C Abstract: The carbon emission trading is an important market-oriented tool in the process of China's carbon neutrality, which makes companies face tremendous pressure to reduce emissions while having strong energy demands. In order to evaluate whether energy prices can be robust predictors of the prices of emission allowances, this study perform extreme bounds analysis (EBA) in four representative markets. The empirical results reveal that energy prices can indeed predict the prices of emission allowances, but the robustly predictive capabilities of different energy prices vary with regions. Among them, thermal coal is the robustly positive predictor for Guangdong, Hubei and Shanghai market; natural gas is the robustly negative predictor for all the four chosen regions; and crude oil can only positively predict Hubei market with robustness. Meanwhile, the horizons that predictions from energy to emission allowance can be performed as well as the predictive coefficients also vary with energy types and regions. And some trading implications are also provided alongside. Keywords: Emission trading market; Energy price; Extreme bounds analysis; Robust prediction (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:82:y:2022:i:c:s1057521922001715 DOI: 10.1016/j.irfa.2022.102210 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.