信用和流动风险冲击下的中国银行业传染分析
Contagion analysis of China's banking industry under the impact of credit and liquidity risk
查看参考文献22篇
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文摘
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银行业信用风险冲击和传染是金融危机的重要导火索之一,而金融危机的加深导致流动性风险冲击会进一步加剧银行业风险.基于中国资产规模最大的50家代表性银行的同业债权债务关系,通过最大熵方法构建了阈值过滤后的银行业双边同业资产-负债关联网络,进一步在完全网络和“核心-边缘”网络下分别模拟了信用风险单冲击以及信用和流动风险双冲击叠加下的银行业风险传染路径、波及范围和程度.结果发现,第一,从风险易感染程度来看,农村商业银行最高,而大型商业银行最低,从风险破坏程度来看,处于网络中心、资产规模大的银行更强;第二,当信用、流动风险二维冲击时,风险传染效将增强,传染阈值也会相应降低;第三,长周期银行业拆借网络分析发现过滤后的中国银行业网络有明显的核心-边缘结构,当市场从完全网络变为核心-边缘网络时,银行体系抵御风险的能力会有所下降.研究结果不仅可以为商业银行自身的风险管理提供建议,而且可以为监管机构风险监控提供借鉴. |
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其他语种文摘
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The contagion of banking credit risk is one of the important triggers of the financial crisis. Based on the inter-bank credit and debt relationship of the 50 representative banks with the largest asset scale in China, this paper constructs the bilateral inter-bank asset liability association network of the banking industry after threshold filtering by using the maximum entropy method. Furthermore, under the complete network and "core- edge" hierarchical network, this paper respectively simulated the credit shock and the double impact of the credit and liquidity shocks. The results show that, first, from the perspective of risk susceptibility, rural commercial banks are the highest, while large commercial banks are the lowest. From the perspective of risk destruction, the financial institutions on the centre of the network and with large asset scale are stronger. Second, when credit and liquidity shocks are superimposed, the risk contagion effect will increase correspondingly, and the infection threshold will be reduced accordingly. Once the liquidity crisis occurs, banks will face serious rollover risk. Third, when the market changes from the complete network structure to the core- edge network structure, the ability of banking system to resist risks will decline. The research results can not only provide suggestions for the risk management of commercial banks themselves, but also provide reference for the regulatory agencies' systematic risk monitoring. |
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来源
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系统工程理论与实践
,2021,41(6):1412-1427 【核心库】
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DOI
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10.12011/SETP2020-2529
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关键词
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信用冲击
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流动性冲击
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风险传染
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债权债务网络
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地址
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1.
中央财经大学管理科学与工程学院, 北京, 100081
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中国科学院数学与系统科学研究院, 北京, 100190
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1000-6788 |
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学科
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社会科学总论 |
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基金
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国家自然科学基金面上项目
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国家金融安全教育部工程研究中心资助
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文献收藏号
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CSCD:7010689
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参考文献 共
22
共2页
|
|
1.
Imbierowicz B. The relationship between liquidity risk and credit risk in banks.
Journal of Banking & Finance,2014,40:242-256
|
CSCD被引
2
次
|
|
|
|
|
2.
舒长江. 基于资金循环流动视角的结构性杠杆与金融脆弱性--理论框架与中国实践.
财经理论与实践,2019,40(1):10-16
|
CSCD被引
1
次
|
|
|
|
|
3.
陈颖. 次贷危机对新资本协议实施的影响.
国际金融研究,2008(10):51-60
|
CSCD被引
2
次
|
|
|
|
|
4.
陈国进. 货币政策、宏观审慎监管与银行系统性风险承担.
系统工程理论与实践,2020,40(6):1419-1438
|
CSCD被引
11
次
|
|
|
|
|
5.
王霞. 基于非参数回归的金融传染检验.
系程理论与实践,2020,40(6):1398-1418
|
CSCD被引
6
次
|
|
|
|
|
6.
Anand K. Filling in the blanks: Network structure and interbank contagion.
Quantitative Finance,2015,15(4):625-636
|
CSCD被引
13
次
|
|
|
|
|
7.
Van Lelyveld I. Finding the core: Network structure in interbank markets.
Journal of Banking & Finance,2014,49:27-40
|
CSCD被引
6
次
|
|
|
|
|
8.
Bargigli L. The multiplex structure of interbank networks.
Quantitative Finance,2015,15(4):673-691
|
CSCD被引
7
次
|
|
|
|
|
9.
Grilli R. Markets connectivity and financial contagion.
Journal of Economic Interaction and Coordination,2015,10(2):287-304
|
CSCD被引
4
次
|
|
|
|
|
10.
Elliott M. Financial networks and contagion.
American Economic Review,2014,104(10):3115-3153
|
CSCD被引
18
次
|
|
|
|
|
11.
Allahrakha M.
Systemic importance indicators for 33 US bank holding companies: An overview of recent data,2015
|
CSCD被引
1
次
|
|
|
|
|
12.
鲍勤. 网络视角下的金融结构与金融风险传染.
系统工程理论与实践,2014,34(9):2202-2211
|
CSCD被引
29
次
|
|
|
|
|
13.
隋聪. 银行间网络连接倾向异质性与风险传染.
国际金融研究,2017(7):44-53
|
CSCD被引
5
次
|
|
|
|
|
14.
Liu A. Interbank contagion: An agent-based model approach to endogenously formed networks.
Journal of Banking & Finance,2020,112:105191
|
CSCD被引
5
次
|
|
|
|
|
15.
Gofman M. Efficiency and stability of a financial architecture with too-interconnected-to-fail institutions.
Journal of Financial Economics,2017,124(1):113-146
|
CSCD被引
2
次
|
|
|
|
|
16.
Acemoglu D. Systemic risk and stability in financial networks.
American Economic Review,2015,105(2):564-608
|
CSCD被引
43
次
|
|
|
|
|
17.
李守伟. 基于复杂网络的银行同业拆借市场稳定性研究.
管理工程学报,2011,25(2):195-199
|
CSCD被引
7
次
|
|
|
|
|
18.
Sarkar A. Liquidity risk, credit risk, and the federal reserve's responses to the crisis.
Financial Markets and Portfolio Management,2009,23(4):335-348
|
CSCD被引
1
次
|
|
|
|
|
19.
Cornett M. Liquidity risk management and credit supply in the financial crisis.
Journal of financial economics,2011,101(2):297-312
|
CSCD被引
1
次
|
|
|
|
|
20.
何奕. 复杂金融网络中的系统性风险与流动性救助:基于不同网络拓扑结构的研究.
系统工程理论与实践,2019,39(6):1385-1393
|
CSCD被引
7
次
|
|
|
|
|
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