The behavior of banks and enterprises in the Credit Risk Transfer (CRT) market determines the diffusion and contagion of credit risk. Research on its contagion evolution mechanism will contribute to establishing financial regulatory strategies. This paper adopts the complex network analysis method and innovatively introduces climate risk influencing factors to explore the credit risk contagion mechanism between banks and enterprises. Based on the susceptible-infected-recovered-susceptible (SIRS) model, a credit risk contagion evolution model is constructed for bank-corporate networks which considers key factors such as risk resistance, capital adequacy, climate change shocks, and climate transition risk. First, the credit risk contagion mechanism between banks and enterprises and the impact of complex network heterogeneity on risk diffusion are analyzed at the theoretical level. On this basis, the advantages of the SIRS model in the study of risk contagion in the CRT market are explored. Subsequently, the evolutionary characteristics of credit risk contagion between bank-corporate credit networks are analyzed using simulation methods. The research results show that: In the bank credit network, the probability of credit risk contagion shows a marginally decreasing characteristic as risk resistance and capital adequacy increase. However, it increases with the probability of credit risk contagion from enterprises to banks and the impacts of climate change. In the enterprise credit network, the probability of credit risk contagion shows a marginally decreasing trend with improvements in information disclosure and market liquidity. However, it increases with climate transition risks and the contagion of credit risk from banks to enterprises, showing a marginally increasing upward trend. The high heterogeneity of the BA scale-free network significantly amplifies the credit risk contagion effects between banks and enterprises, while the relative homogeneity of the WS small-world network can, to some extent, mitigate the concentration of credit risk contagion.
References
[1]
Allen, F. and Carletti, E. (2006) Credit Risk Transfer and Contagion. Journal of Monetary Economics, 53, 89-111. https://doi.org/10.1016/j.jmoneco.2005.10.004
[2]
Elsinger, H., Lehar, A. and Summer, M. (2006) Systemically Important Banks: An Analysis for the European Banking System. International Economics and Economic Policy, 3, 73-89. https://doi.org/10.1007/s10368-006-0046-4
[3]
Brunnermeier, M.K. (2009) Deciphering the Liquidity and Credit Crunch 2007-2008. Journal of Economic Perspectives, 23, 77-100. https://doi.org/10.1257/jep.23.1.77
[4]
Gorton, G. and Metrick, A. (2012) Getting up to Speed on the Financial Crisis: A One-Weekend-Reader’s Guide. Journal of Economic Literature, 50, 128-150. https://doi.org/10.1257/jel.50.1.128
[5]
Bemanke, B. and Gertler, M. (1989) Agency Costs, Net Worth, and Business Fluctuations. American Economic Review, 79, 14-31.
[6]
Bernanke, B.S., Gertler, M. and Gilchrist, S. (1994) The Financial Accelerator and the Flight to Quality. https://doi.org/10.3386/w4789
[7]
Bernanke, B.S., Gertler, M. and Gilchrist, S. (1999) The Financial Accelerator in a Quantitative Business Cycle Framework. Handbook of Macroeconomics, 1, 1341-1393. https://doi.org/10.1016/S1574-0048(99)10034-X
[8]
Georg, C.P. (2013) The Effect of the Interbank Network Structure on Contagion and Common Shocks. Journal of Banking & Finance, 37, 2216-2228. https://doi.org/10.1016/j.jbankfin.2013.02.032
[9]
Becher, C., Millard, S. and Soramaki, K. (2008) The Network Topology of CHAPS Sterling. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1319277
[10]
Wang, L., Huang, Z. and Wang, Y. (2023) Bank Shareholder Network and Board Governance: Evidence from Chinese Commercial Banks. Journal of Innovation & Knowledge, 8, Article 100412. https://doi.org/10.1016/j.jik.2023.100412
[11]
Dungey, M., Flavin, T., O’Connor, T. and Wosser, M. (2022) Non-Financial Corporations and Systemic Risk. Journal of Corporate Finance, 72, Article 102129. https://doi.org/10.1016/j.jcorpfin.2021.102129
[12]
Laeven, L., Ratnovski, L. and Tong, H. (2016) Bank Size, Capital, and Systemic Risk: Some International Evidence. Journal of Banking & Finance, 69, S25-S34. https://doi.org/10.1016/j.jbankfin.2015.06.022
[13]
Cheng, M. and Qu, Y. (2020) Does Bank Fintech Reduce Credit Risk? Evidence from China. Pacific-Basin Finance Journal, 63, Article 101398. https://doi.org/10.1016/j.pacfin.2020.101398
[14]
Qian, Q., Chao, X. and Feng, H. (2023) Internal or External Control? How to Respond to Credit Risk Contagion in Complex Enterprises Network. International Review of Financial Analysis, 87, Article 102604. https://doi.org/10.1016/j.irfa.2023.102604
[15]
Ma, J.L., Zhu, S.S. and Wu, Y. (2021) Joint Effects of the Liability Network and Portfolio Overlapping on Systemic Financial Risk: Contagion and Rescue. Quantitative Finance, 21, 753-770. https://doi.org/10.1080/14697688.2020.1802054
[16]
Rishehchi Fayyaz, M., Rasouli, M.R. and Amiri, B. (2021) A Data-Driven and Network-Aware Approach for Credit Risk Prediction in Supply Chain Finance. Industrial Management & Data Systems, 121, 785-808. https://doi.org/10.1108/imds-01-2020-0052
[17]
Bougheas, S. and Kirman, A.P. (2015) Complex Financial Networks and Systemic Risk: A Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2436826
[18]
Varotto, S. and Zhao, L. (2018) Systemic risk and bank size. Journal of International Money and Finance, 82, 45-70. https://doi.org/10.1016/j.jimonfin.2017.12.002
[19]
Pagnottoni, P., Spelta, A., Flori, A. and Pammolli, F. (2022) Climate Change and Financial Stability: Natural Disaster Impacts on Global Stock Markets. Physica A: Statistical Mechanics and its Applications, 599, Article 127514. https://doi.org/10.1016/j.physa.2022.127514
[20]
May, R.M., Levin, S.A. and Sugihara, G. (2008) Ecology for bankers. Nature, 451, 893-894. https://doi.org/10.1038/451893a
[21]
Huang, Q.A., Zhao, J.C. and Wu, X.Q. (2022) Financial Risk Propagation between Chinese and American Stock Markets Based on Multilayer Networks. PhysicaA: StatisticalMechanicsandItsApplications, 586, Article 126445. https://doi.org/10.1016/j.physa.2021.126445
[22]
Wang, L., Li, S. and Chen, T. (2019) Investor Behavior, Information Disclosure Strategy and Counterparty Credit Risk Contagion. Chaos, Solitons & Fractals, 119, 37-49. https://doi.org/10.1016/j.chaos.2018.12.007
[23]
Allen, F. and Gale, D. (2000) Financial Contagion. Journal of Political Economy, 108, 1-33. https://doi.org/10.1086/262109
[24]
Freixas, X., Parigi, B.M. and Rochet, J. (2000) Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank. Journal of Money, Credit and Banking, 32, 611-638. https://doi.org/10.2307/2601198
[25]
Liu, X., Liu, J. and Hao, Y. (2024) Climate Change Shocks and Credit Risk of Financial Institutions: Evidence from China’s Commercial Banks. Emerging Markets Finance and Trade, 60, 1392-1406. https://doi.org/10.1080/1540496x.2023.2278659
[26]
Capasso, G., Gianfrate, G. and Spinelli, M. (2020) Climate Change and Credit Risk. Journal of Cleaner Production, 266, Article 121634. https://doi.org/10.1016/j.jclepro.2020.121634
[27]
Ugolini, A., Reboredo, J.C. and Ojea-Ferreiro, J. (2024) Is Climate Transition Risk Priced into Corporate Credit Risk? Evidence from Credit Default Swaps. Research in International Business and Finance, 70, Article 102372. https://doi.org/10.1016/j.ribaf.2024.102372
