基于多层网络的银行间市场信用拆借智能风险传染机制
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摘要
基于多层网络结构对银行间市场进行分析研究,有利于规避或减弱对金融市场的风险冲击。基于信用拆借业务场景模拟的测试数据,结合银行间市场多层网络结构和复杂网络分析方法,从不同角度对银行间市场中重要节点进行判断识别,同时计算层间的Jaccard相似系数数和机构间皮尔逊相似性系数,从宏观和微观角度来衡量银行间市场的风险传染性。实验结果表明,中国银行、国家开发银行等大型国有金融机构系统重要性较高,且机构间的相似度越大,风险传染性就越大。因此,通过计算网络层内的重要性节点衡量指标,全面完整地对整个系统的风险传染情况进行分析,可协助监管部门实现对系统重要性机构的精准监测。同时,从层间分析与层内分析两个角度出发,全面衡量受到金融冲击后的机构间风险传染程度,可为监管机构提供政策上的建议。
Analysis and research on interbank market based on multi-layer network structure is conducive to avoiding or weakening the risk impact on financial market. Based on test data simulated by credit lending business scenario, combined with the multi-layer network structure and complex network analysis method of interbank market, the important nodes in interbank market were judged and identified from different angles, meanwhile Jaccard similarity coefficient between the layers and inter-institution Pearson similarity coefficient were calculated and the infectousness of risk contagion of interbank market was measured from macroscopic and microscopic perspectives. The experimental results show that large-scale state-owned financial institutions such as Bank of China and China Development Bank are of high importance in the system, and the greater the similarity between institutions, the greater the infectiousness of risk contagion. Therefore, by calculating the important node measure index in the network layer, comprehensive and complete analysis of the risk contagion of the entire system can help the regulators to achieve accurate monitoring of important institutions in the system. At the same time, from the perspectives of inter-layer analysis and intra-layer analysis, comprehensive measurement of the infectious degree of risk contagion between institutions after financial shock provides policy advice to regulators.
Analysis and research on interbank market based on multi-layer network structure is conducive to avoiding or weakening the risk impact on financial market. Based on test data simulated by credit lending business scenario, combined with the multi-layer network structure and complex network analysis method of interbank market, the important nodes in interbank market were judged and identified from different angles, meanwhile Jaccard similarity coefficient between the layers and inter-institution Pearson similarity coefficient were calculated and the infectousness of risk contagion of interbank market was measured from macroscopic and microscopic perspectives. The experimental results show that large-scale state-owned financial institutions such as Bank of China and China Development Bank are of high importance in the system, and the greater the similarity between institutions, the greater the infectiousness of risk contagion. Therefore, by calculating the important node measure index in the network layer, comprehensive and complete analysis of the risk contagion of the entire system can help the regulators to achieve accurate monitoring of important institutions in the system. At the same time, from the perspectives of inter-layer analysis and intra-layer analysis, comprehensive measurement of the infectious degree of risk contagion between institutions after financial shock provides policy advice to regulators.
引文
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[15] 范小云,刘开林.银行流动性过剩的自愿性与非自愿性因素辨析——兼论对货币政策的影响[J].当代经济科学,2007,29(5):68-74.(FAN X Y,LIU K L.Analysis of voluntary and involuntary factors of excess liquidity of banks — also on the influence of monetary policy[J].Contemporary Economic Science,2007,29(5):68-74.)
[16] BARGIGLI L,IASIO G D,INFANTE L,et al.The multiplex structure of interbank networks[J].SSRN Electronic Journal,2013,15(4):673-691.
[17] MONTAGNA M,KOK C.Multi-layered interbank model for assessing systemic risk[EB/OL].[2018- 03- 20].https://www.files.ethz.ch/isn/170406/KWP_1873.pdf.
[2] CRAIG B,von PETER G.Interbank tiering and money center banks[J].Journal of Financial Intermediation,2014,23(3):322-347.
[3] SORAM?KI K,BECH M L,ARNOLD J,et al.The topology of interbank payment flows[J].Physica A:Statistical Mechanics & Its Applications,2006,379(1):317-333.
[4] BECH M L,ATALAY E.The topology of the federal funds market[J].Physica A:Statistical Mechanics & Its Applications,2010,389(22):5223-5246.
[5] DEGRYSE H,NGUYEN G.Interbank exposures:an empirical examination of contagion risk in the belgian banking system[EB/OL].[2018- 03- 20].https://www.ijcb.org/journal/ijcb07q2a5.pdf.
[6] VELD D I,van LELYVELD I.Finding the core:network structure in interbank markets[J].Journal of Banking & Finance,2014,49(C):27-40.
[7] FRICKE D,LUX T.Core-periphery structure in the overnight money market:evidence from the e-MID trading platform[J].Computational Economics,2015,45(3):359-395.
[8] LANGFIELD S,LIU Z,OTA T.Mapping the UK interbank system[J].Journal of Banking & Finance,2014,45(8):288-303.
[9] ALDASORO I,ALVES I.Multiplex interbank networks and systemic importance:an application to European data[J].Journal of Financial Stability,2018,35:17-37.
[10] 廖为鼎,陈一非.基于网络分析法的我国银行间风险传染效应研究[J].金融监管研究,2014(10):59-76.(LIAO W D,CHEN Y F.Research on China's inter-bank risk contagion effect based on network analysis[J].Financial Regulation Research,2014(10):59-76.)
[11] ALLEN F,GALE D.Financial contagion[J].Journal of Political Economy,2000,108(1):1-33.
[12] UPPER C,WORMS A.Estimating bilateral exposures in the German interbank market:is there a danger of contagion?[J].European Economic Review,2002,48(4):827-849.
[13] FREIXAS X,PARIGI B M,ROCHET J C.Systemic risk,interbank relations,and liquidity provision by the central bank[J].Journal of Money Credit & Banking,2000,32(3):611-638.
[14] FURFINE C H.Interbank exposures:quantifying the risk of contagion[J].Journal of Money Credit & Banking,2003,35(1):111-128.
[15] 范小云,刘开林.银行流动性过剩的自愿性与非自愿性因素辨析——兼论对货币政策的影响[J].当代经济科学,2007,29(5):68-74.(FAN X Y,LIU K L.Analysis of voluntary and involuntary factors of excess liquidity of banks — also on the influence of monetary policy[J].Contemporary Economic Science,2007,29(5):68-74.)
[16] BARGIGLI L,IASIO G D,INFANTE L,et al.The multiplex structure of interbank networks[J].SSRN Electronic Journal,2013,15(4):673-691.
[17] MONTAGNA M,KOK C.Multi-layered interbank model for assessing systemic risk[EB/OL].[2018- 03- 20].https://www.files.ethz.ch/isn/170406/KWP_1873.pdf.