Ying Huang, Juan Hu, and Jing Chen
School of Foreign Languages, Wuhan City Polytechnic, Wuhan 430064, China
Received: March 2, 2026
Accepted: April 1, 2026
Publication Date: June 1, 2026
Spillover Networks in Time, High-, Medium- and Low- Frequency Domains.
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Download Citation: BibTeX | http://dx.doi.org/10.6180/jase.202609_32.064
The diverse roles of green financial sub-markets and their dynamic risk spillovers to the carbon market are important to explain the systemic risks of Chinese low-carbon transition. We employ a Time-Varying Parameter Vector Autoregression (TVP-VAR) model with time-frequency decomposition to explore the connections in China’s carbon-green finance system between January 2016 and January 2025. The findings indicate major bidirectional asymmetric spillovers, with the greater impacts of green financial markets on the carbon market. Particularly, functional heterogeneity is strong across the green financial sub-markets. Green equity markets serve as persistent risk transmitters whereas green bonds are transitional, changing from short-term risk transmitters to long-term stabilizers. The carbon market is regularly a net risk recipient due to its policy-driven nature. On the dynamic features, cross-market linkages are highly time-frequency asymmetries, dominated by short-term speculative spillovers and amplified by extreme events and policy shifts. Moreover, there are clear temporal heterogeneities in the risk transmission paths, where short-run flows are sentiment-led and long-run are fundamentals-led. Understanding these dynamics is crucial for both policy-makers and investors in dealing with systemic climate-finance risks.
Keywords: carbon market; green financial market; dynamic risk spillovers; TVP-VAR-DY; TVP-VAR-BK; Computer network
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