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Counterparty Risk Contagion Model of Carbon Quota Based on Asset Price Reduction

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  • Tingqiang Chen

    (School of Economics and Management, Nanjing Tech University, Nanjing 211816, China
    School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Yuejuan Hou

    (School of Economics and Management, Nanjing Tech University, Nanjing 211816, China)

  • Lei Wang

    (School of Economics and Management, Nanjing Tech University, Nanjing 211816, China)

  • Zeyu Li

    (School of Economics and Management, Nanjing Tech University, Nanjing 211816, China)

Abstract

Driven by the “double carbon” goal, the sale of financial assets at reduced prices by firms due to carbon emission constraints is bound to aggravate the uncertainty and volatility of carbon trading among firms, and potentially create counterparty risk contagion. In view of this, this paper considers the sensitivity of the transaction of corporate financial assets, the transaction price of carbon quotas, and corporate carbon performance; constructs a network model for the risk contagion of carbon quota counterparties; theoretically discusses the risk formation and infection mechanism of carbon quota counterparties; and calculates and simulates the evolutionary characteristics of the risk contagion of carbon quota counterparties. The main research conclusions are as follows. (1) In the interfirm debt network, the sensitivity to the price of selling the financial asset, the probability of credit risk contagion of carbon quotas among firms, the cumulative proportion of assets sold, and the proportion of rational investors in the financial market exert a decreasing phenomenon on the risk of carbon quota counterparties. In addition, the corporate carbon performance shows a marginal increasing phenomenon. (2) When multiple factors intersect, the proportion of rational investors in the financial market has the greatest influence on the formation of the carbon quota counterparty risk, whereas the effect of corporate carbon performance has the least. Corporate carbon risk awareness has the greatest effect on the risk contagion of carbon quota counterparties, whereas the trading price of the carbon quota has the least influence. In addition, the total score of the interfirm assessment has a great impact on the trend and range of the risk contagion of carbon quota counterparties. (3) Corporate carbon risk awareness and the carbon quota trading price have a marginally decreasing effect on the risk contagion of carbon quota counterparties, and corporate carbon performance and the total score of interfirm assessment have a marginally increasing effect. This study has important theoretical and practical significance for preventing interfirm counterparty risk contagion under the double carbon target.

Suggested Citation

  • Tingqiang Chen & Yuejuan Hou & Lei Wang & Zeyu Li, 2023. "Counterparty Risk Contagion Model of Carbon Quota Based on Asset Price Reduction," Sustainability, MDPI, vol. 15(14), pages 1-35, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11377-:d:1199644
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    References listed on IDEAS

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    1. Tingqiang Chen & Qinghao Yang & Yutong Wang & Suyang Wang, 2020. "Double-Layer Network Model of Bank-Enterprise Counterparty Credit Risk Contagion," Complexity, Hindawi, vol. 2020, pages 1-25, October.
    2. Pei Mu & Tingqiang Chen & Kun Pan & Meng Liu & Shaojian Qu, 2021. "A Network Evolution Model of Credit Risk Contagion between Banks and Enterprises Based on Agent-Based Model," Journal of Mathematics, Hindawi, vol. 2021, pages 1-12, November.
    3. Juhyun Jung & Kathleen Herbohn & Peter Clarkson, 2018. "Carbon Risk, Carbon Risk Awareness and the Cost of Debt Financing," Journal of Business Ethics, Springer, vol. 150(4), pages 1151-1171, July.
    4. Mizuno, Takayuki & Ohnishi, Takaaki & Watanabe, Tsutomu, 2016. "Structure of global buyer-supplier networks and its implications for conflict minerals regulations," HIT-REFINED Working Paper Series 38, Institute of Economic Research, Hitotsubashi University.
    5. Yang, Chunpeng & Li, Jinfang, 2013. "Investor sentiment, information and asset pricing model," Economic Modelling, Elsevier, vol. 35(C), pages 436-442.
    6. Zhang, Yajun, 2022. "How Economic Performance of OECD economies influences through Green Finance and Renewable Energy Investment Resources?," Resources Policy, Elsevier, vol. 79(C).
    7. He, Jianmin & Sui, Xin & Li, Shouwei, 2016. "An endogenous model of the credit network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 1-14.
    8. Guiliang Zha & Yongqing Li & Qingliang Tang, 2022. "Impacts of Emissions Trading Scheme Initiatives on Corporate Carbon Proactivity and Financial Performance," JRFM, MDPI, vol. 15(11), pages 1-18, November.
    9. Xiaoting Ling & Lijuan Yan & Deming Dai, 2022. "Green Credit Policy and Investment Decisions: Evidence from China," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    10. Tingqiang Chen & Suyang Wang, 2023. "Incomplete information model of credit default of micro and small enterprises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2956-2974, July.
    11. Sui, Xin & Li, Liang & Chen, Xiaohui, 2020. "Risk contagion caused by interactions between credit and guarantee networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    12. Liu, Anqi & Paddrik, Mark & Yang, Steve Y. & Zhang, Xingjia, 2020. "Interbank contagion: An agent-based model approach to endogenously formed networks," Journal of Banking & Finance, Elsevier, vol. 112(C).
    13. Chen, Tingqiang & Wang, Yutong & Zeng, Qianru & Luo, Jun, 2020. "Network model of credit risk contagion in the interbank market by considering bank runs and the fire sale of external assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    14. Arora, Navneet & Gandhi, Priyank & Longstaff, Francis A., 2012. "Counterparty credit risk and the credit default swap market," Journal of Financial Economics, Elsevier, vol. 103(2), pages 280-293.
    15. Chi-Wei Su & Xu-Yu Cai & Ran Tao, 2020. "Can Stock Investor Sentiment Be Contagious in China?," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    16. Pi, Xiaochen & Tang, Longkun & Chen, Xiangzhong, 2021. "A directed weighted scale-free network model with an adaptive evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    17. Qian, Qian & Feng, Hairong & Gu, Jing, 2021. "The influence of risk attitude on credit risk contagion—Perspective of information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    18. Li, Gang & Zhang, Chu, 2019. "Counterparty credit risk and derivatives pricing," Journal of Financial Economics, Elsevier, vol. 134(3), pages 647-668.
    19. Song, Malin & Zheng, Huanyu & Shen, Zhiyang, 2023. "Whether the carbon emissions trading system improves energy efficiency – Empirical testing based on China's provincial panel data," Energy, Elsevier, vol. 275(C).
    20. Ding Ding & Liyan Han & Libo Yin, 2017. "Systemic risk and dynamics of contagion: a duplex inter-bank network," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1435-1445, September.
    21. Jia, Zhijie & Lin, Boqiang, 2020. "Rethinking the choice of carbon tax and carbon trading in China," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    22. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2007. "Network models and financial stability," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 2033-2060, June.
    23. Ting-Qiang Chen & Jian-Min He, 2012. "A Network Model of Credit Risk Contagion," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-13, December.
    24. Chen, Tingqiang & Wang, Jiepeng & Liu, Haifei & He, Yuanping, 2019. "Contagion model on counterparty credit risk in the CRT market by considering the heterogeneity of counterparties and preferential-random mixing attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 458-480.
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