{"id":7413,"date":"2026-06-01T09:49:21","date_gmt":"2026-06-01T01:49:21","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=7413"},"modified":"2026-06-01T12:32:13","modified_gmt":"2026-06-01T04:32:13","slug":"jase-202609-32-064","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202609-32-064","title":{"rendered":"Functional Heterogeneity and Dynamic Risk Spillovers in China’s Carbon-Green Finance System: A Time-Frequency TVP-VAR Analysis"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 32<\/a><\/p>\n<\/div>\n\n\n\n

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Ying Huang, Juan Hu<\/i><\/a>, and Jing Chen<\/p>\n\n\n\n

School of Foreign Languages, Wuhan City Polytechnic, Wuhan 430064, China<\/p>\n<\/div>\n\n\n\n

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Received: March 2, 2026
Accepted: April 1, 2026
Publication Date: June 1, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Spillover Networks in Time, High-, Medium- and Low- Frequency Domains.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:\u00a0 BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202609_32.064<\/a>\u00a0\u00a0<\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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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\u2019s 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.<\/p>\n\n\n\n

Keywords: carbon market; green financial market; dynamic risk spillovers; TVP-VAR-DY; TVP-VAR-BK; Computer network<\/em><\/p>\n\n\n\n

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  1. [1] N. Koch, (2014) \u201cDynamic linkages among carbon, energy and financial markets: a smooth transition approach\u201d Applied Economics 46(7): 715\u2013729. DOI: 10.1080\/00036846.2013.854301.<\/li>\n
  2. [2] X. Tan, K. Sirichand, A. Vivian, and X. Wang, (2020) \u201cHow connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics\u201d Energy Economics 90: 104870. DOI: 10.1016\/j.eneco.2020.104870.<\/li>\n
  3. [3] J. Jin, L. Han, L. Wu, and H. Zeng, (2020) \u201cThe hedging effect of green bonds on carbon market risk\u201d International Review of Financial Analysis 71: 101509. DOI: 10.1016\/j.irfa.2020.101509.<\/li>\n
  4. [4] W. Hanif, J. A. Hernandez, W. Mensi, S. H. Kang, G. S. Uddin, and S.-M. Yoon, (2021) \u201cNonlinear dependence and connectedness between clean\/renewable energy sector equity and European emission allowance prices\u201d Energy Economics 101: 105409. DOI: 10.1016\/j.eneco.2021.105409.<\/li>\n
  5. [5] Y. Zhang and M. Umair, (2023) \u201cExamining the interconnectedness of green finance: an analysis of dynamic spillover effects among green bonds, renewable energy, and carbon markets\u201d Environmental Science and Pollution Research 30(3): 77605\u201377621. DOI: 10.1007\/s11356-023-27870-w.<\/li>\n
  6. [6] I. Chatziantoniou, E. J. A. Abakah, D. Gabauer, and A. K. Tiwari, (2022) \u201cQuantile time\u2013frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets\u201d Journal of Cleaner Production 361: 132088. DOI: 10.1016\/j.jclepro.2022.132088.<\/li>\n
  7. [7] R. Wu and Z. Qin, (2024) \u201cAsymmetric volatility spillovers among new energy, ESG, green bond and carbon markets\u201d Energy 292: 130504. DOI: 10.1016\/j.energy.2024.130504.<\/li>\n
  8. [8] Z. Huang, X. Ding, and Y. Wang, (2026) \u201cRisk spillover and network connectedness analysis of green financial and related financial markets: evidence from China\u201d Humanities and Social Sciences Communications 13(1): 344. DOI: 10.1057\/s41599-026-06706-1.<\/li>\n
  9. [9] J. Deng, Y. Zheng, and X. Gu et al., (2023) \u201cResearch on the Spillover Effects between China\u2019s Carbon Market and Green Finance Market\u201d Financial Theory & Practice 44(7): 48\u201359. DOI: 10.3969\/j.issn.1003-4625.2023.07.005.<\/li>\n
  10. [10] L. Yan and W. Han, (2025) \u201cThe complexity of connection between green bonds and carbon markets: New evidence from China\u201d Finance Research Letters 84: 107790. DOI: 10.1016\/j.frl.2025.107790.<\/li>\n
  11. [11] T. Hui, Z. Wang, and Z. He, (2025) \u201cResearch on the Spillover Effects of China\u2019s Carbon Market and Green Finance Market\u201d Soft Science 39(6): 17. DOI: 10.13956\/j.ss.1001-8409.2025.06.17.<\/li>\n
  12. [12] S. Qi, L. Pang, X. Li, and L. Huang, (2025) \u201cThe dynamic connectedness in the \u201ccarbon\u2013energy\u2013green finance\u201d system: The role of climate policy uncertainty and artificial intelligence\u201d Energy Economics 143: 108241. DOI: 10.1016\/j.eneco.2025.108241.<\/li>\n
  13. [13] X. Wang and M. Liu, (2025) \u201cResearch on Risk Spillover Effects Among Carbon\u2013Energy\u2013Green Finance Markets\u201d Distributed Energy 10(4): 24\u201334. DOI: 10.16513\/j.2096-2185.DE.25100017.<\/li>\n
  14. [14] W. Jiang, L. Dong, and X. Liu, (2023) \u201cHow does COVID-19 affect the spillover effects of green finance, carbon markets, and renewable\/non-renewable energy markets? Evidence from China\u201d Energy 281: 128351. DOI: 10.1016\/j.energy.2023.128351.<\/li>\n
  15. [15] S. Agarwal and P. Padhi, (2025) \u201cConnectedness among green, brown, technology, and carbon markets: Insights from time-varying models\u201d International Review of Economics & Finance: 104762. DOI: 10.1016\/j.iref.2025.104762.<\/li>\n
  16. [16] F. X. Diebold and K. Y\u0131lmaz, (2012) \u201cBetter to give than to receive: Predictive directional measurement of volatility spillovers\u201d International Journal of Forecasting 28(1): 57\u201366. DOI: 10.1016\/j.ijforecast.2011.02.006.<\/li>\n
  17. [17] N. Antonakakis, I. Chatziantoniou, and D. Gabauer, (2020) \u201cRefined measures of dynamic connectedness based on time-varying parameter vector autoregressions\u201d Journal of Risk and Financial Management 13(4): 84. DOI: 10.3390\/jrfm13040084.<\/li>\n
  18. [18] I. Chatziantoniou, D. Gabauer, and R. Gupta, (2023) \u201cIntegration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach\u201d Resources Policy 84: 103729. DOI: 10.1016\/j.resourpol.2023.103729.<\/li>\n
  19. [19] J. Barun\u00edk and T. K\u0159ehl\u00edk, (2018) \u201cMeasuring the frequency dynamics of financial connectedness and systemic risk\u201d Journal of Financial Econometrics 16(2): 271\u2013296. DOI: 10.1093\/jjfinec\/nby001.<\/li>\n
  20. [20] F. X. Diebold and K. Y\u0131lmaz, (2014) \u201cOn the network topology of variance decompositions: Measuring the connectedness of financial firms\u201d Journal of Econometrics 182(1): 119\u2013134. DOI: 10.1016\/j.jeconom.2014.04.012.<\/li>\n
  21. [21] W. Mensi, X. V. Vo, H.-U. Ko, and S. H. Kang, (2023) \u201cFrequency spillovers between green bonds, global factors and stock market before and during COVID-19 crisis\u201d Economic Analysis and Policy 77: 558\u2013580. DOI: 10.1016\/j.eap.2022.12.010.<\/li>\n
  22. [22] Y. Wang, X. Zhao, and J. Shang, (2025) \u201cDynamic risk spillover in green financial markets: A wavelet frequency analysis from China\u201d Energy Economics 143: 108301. DOI: 10.1016\/j.eneco.2025.108301.<\/li>\n
  23. [23] M. Zhao and H. Park, (2024) \u201cQuantile time-frequency spillovers among green bonds, cryptocurrencies, and conventional financial markets\u201d International Review of Financial Analysis 93: 103198. DOI: 10.1016\/j.irfa.2024.103198.<\/li>\n
  24. [24] J. Barun\u00edk and M. Ellington, (2024) \u201cPersistence in financial connectedness and systemic risk\u201d European Journal of Operational Research 314(1): 393\u2013407. DOI: 10.1016\/j.ejor.2023.11.023.<\/li>\n
  25. [25] X. Jin, (2025) \u201cExtreme Risk Connectedness and its Determinants Between Carbon, Green Finance and Energy Markets\u201d Asia-Pacific Financial Markets: 1\u201334. DOI: 10.1007\/s10690-025-09536-4.<\/li>\n
  26. [26] P. Maneejuk, W. Huang, and W. Yamaka, (2025) \u201cAsymmetric volatility spillover effects from energy, agriculture, green bond, and financial market uncertainty on carbon market during major market crisis\u201d Energy Economics 145: 108430. DOI: 10.1016\/j.eneco.2025.108430.<\/li>\n
  27. [27] Q. Li, (2025) \u201cFinancial stress and idiosyncratic risk spillovers in global carbon\u2013energy\u2013green finance markets\u201d Finance Research Letters: 109362. DOI: 10.1016\/j.frl.2025.109362.<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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