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复杂系统与复杂性科学  2024, Vol. 21 Issue (3): 55-61    DOI: 10.13306/j.1672-3813.2024.03.008
  复杂网络 本期目录 | 过刊浏览 | 高级检索 |
具有CDS的动态多层网络银行系统性风险研究
汤淼, 范宏
东华大学旭日工商管理学院,上海 200051
Investigating Banking Systemic Risk of Dynamic Multilayer Networks with CDS
TANG Miao, FAN Hong
Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China
全文: PDF(2445 KB)  
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摘要 美国次贷危机表明CDS对银行系统性风险有很大影响,但CDS如何影响银行系统性风险的机理还未明。因此,构建了一个具有CDS交互作用的动态多层银行网络模型,研究两种经济环境下的CDS对银行系统的双重影响。研究结果表明:经济平稳时期,CDS有风险吸收作用,降低银行系统性风险;经济波动时期,银行因CDS释放的超额风险资产会转变为新的系统性风险;CDS的规模与银行系统性风险呈负相关关系,且规模存在临界值。
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汤淼
范宏
关键词 信用违约互换(CDS)系统性风险银企间信用风险风险转移    
Abstract:The subprime mortgage crisis in the United States shows that CDS significantly impacts banking systemic risk, but the mechanism of how CDS affects banking systemic risk is still unclear. This paper first constructs a dynamic multi-layer banking network model with CDS interactions to study the dual impact of CDS on the banking system in both volatile and stable economic environments. The results show that when the economy is stable, CDS has a positive absorption effect, which successfully transfers the risk and reduces the banking systemic risk; When the economy is volatile, the excess risk assets released by banks due to CDS are transformed into new systemic risk; the size of CDS is negatively correlated with the banking systemic risk and there is a critical value of size.
Key wordscredit default swap(CDS)    systemic risk    bank-firm credit risk    risk transfer
收稿日期: 2022-12-09      出版日期: 2024-11-07
ZTFLH:  F830  
  N94  
基金资助:国家自然科学基金(71371046);上海市自然科学基金(19ZR1402100)
通讯作者: 范宏(1971-),女,上海人,博士,教授,主要研究方向为复杂经济系统建模与分析、金融系统性风险分析。   
作者简介: 汤淼(1993-),女,黑龙江双鸭山人,博士研究生,主要研究方向为复杂经济系统建模与分析,金融系统性风险分析。
引用本文:   
汤淼, 范宏. 具有CDS的动态多层网络银行系统性风险研究[J]. 复杂系统与复杂性科学, 2024, 21(3): 55-61.
TANG Miao, FAN Hong. Investigating Banking Systemic Risk of Dynamic Multilayer Networks with CDS[J]. Complex Systems and Complexity Science, 2024, 21(3): 55-61.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2024.03.008      或      https://fzkx.qdu.edu.cn/CN/Y2024/V21/I3/55
[1] 方意,赵胜民,黄丽灵,等.房地产市场与银行业系统性风险[J].管理科学学报,2021,24(11):26-43.
FANG Y, ZHAO S M, HUANG L L, et al. The real estate market and systemic risk in the banking system[J]. Journal of Management Sciences in China, 2021,24(11):26-43.
[2] LADLEY D. Contagion and risk-sharing on the inter-bank market[J]. Journal of Economic Dynamics and Control, 2013, 37(7): 1384-1400.
[3] MITCHENER K J, RICHARDSON G. Network contagion and interbank amplification during the great depression[J]. Journal of Political Economy, 2019, 127(2):465-507.
[4] LEVENTIDES J, LOUKAKI K, PAPAVASSILOOU V G. Simulating financial contagion dynamics in random interbank networks[J]. Journal of Economic Behavior & Organization, 2019, 158: 500-525.
[5] BARGIGLI L, GALLEGATI M, RICCETTI L, et al. Network analysis and calibration of the “leveraged network-based financial accelerator”[J]. Journal of Economic Behavior & Organization, 2014, 99: 109-125.
[6] SILVA T C, ALEXANDRE M D S, TABAK B M. Bank lending and systemic risk: a financial-real sector network approach with feedback[J]. Journal of Financial Stability, 2018, 38: 98-118.
[7] SHAN C, TANG D Y, YAN H, et al. Credit default swaps and bank regulatory capital[J]. Review of Finance, 2021, 25(1): 121-152.
[8] DANIS A, GAMBA A. The real effects of credit default swaps[J]. Journal of Financial Economics, 2018, 127(1): 51-76.
[9] 陈庭强,周文静,童毛弟,等.融合CDS网络的银行间信用风险传染模型研究[J].中国管理科学,2020,28(6):24-37.
CHEN T Q, ZHOU W J, TONG M D, et al. Research on the model of interbank credit risk contagion by fusing CDS networks[J]. Chinese Journal of Management Science,2020,28(6):24-37.
[10] ALLEN F, CARLETTI E. Credit risk transfer and contagion[J]. Journal of Monetary Economics, 2006, 53(1): 89-111.
[11] WAGNER W, MARSH I W. Credit risk transfer and financial sector stability[J]. Journal of Financial Stability, 2006, 2(2): 173-193.
[12] D’ERRICO M, BATTISTON S, PELTONEN T, et al. How does risk flow in the credit default swap market?[J]. Journal of Financial Stability, 2018, 35: 53-74.
[13] THORNTON J, DI TOMMASO C. Credit default swaps and regulatory capital relief: evidence from European banks[J]. Finance Research Letters, 2018, 26: 255-260.
[14] Brunetti C, Harris J H, Mankad S, et al. Interconnectedness in the interbank market[J]. Journal of Financial Economics, 2019, 133(2): 520-538.
[15] AL-OWN B, MINHAT M, GAO S. Stock options and credit default swaps in risk management[J].Journal of International Financial Markets, Institutions, and Money, 2018,53(3):200-214.
[16] BO L, CAPPONI A. Counterparty risk for CDS: default clustering effects[J]. Journal of Banking & Finance, 2015, 52:29-42.
[17] SCHULDENZUCKER S, SEUKEN S, BATTISTON S. Default ambiguity: credit default swaps create new systemic risks in financial networks[J]. Management Science, 2020, 66(5): 1981-1998.
[18] CATULLO E, GALLEGATI M, PALESTRINI A. Towards a credit network based early warning indicator for crises[J]. Journal of Economic Dynamics and Control, 2015, 50: 78-97.
[19] IORI G, JAFAREY S, PADILLA F G. Systemic risk on the interbank market[J]. Journal of Economic Behavior & Organization, 2006, 61(4): 525-542.
[20] GATTI D D, GALLEGATI M, GREENWALD B, et al. The financial accelerator in an evolving credit network[J]. Journal of Economic Dynamics and Control, 2010, 34(9): 1627-1650.
[21] RICCETTI L,RUSSO A,GALLEGATI M. Leveraged network-based financial accelerator[J]. Journal of Economic Dynamics and Control, 2013, 37(8): 1626-1640.
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