基于共同持有资产的银行间接关联网络研究

doi:10.16381/j.cnki.issn1003-207x.2019.11.003

中国管理科学 ›› 2019, Vol. 27 ›› Issue (11): 23-30.doi: 10.16381/j.cnki.issn1003-207x.2019.11.003

基于共同持有资产的银行间接关联网络研究

王超¹, 何建敏², 马静³

1. 南京农业大学金融学院, 江苏南京 210095;
2. 东南大学经济管理学院, 江苏南京 211189;
3. 南京财经大学MBA教育中心, 江苏南京 210023

收稿日期:2018-05-30 修回日期:2018-08-28 出版日期:2019-11-20 发布日期:2019-11-28
通讯作者: 王超(1990-),男(汉族),山东青岛人,南京农业大学金融学院,讲师,博士,研究方向:金融工程,E-mail:hejianminedu@163.com. E-mail:hejianminedu@163.com
基金资助:
国家自然科学基金资助项目（71971055）

Indirect Correlation Network between Banks Based on Common Assets

WANG Chao¹, HE Jian-min², MA Jing³

1. School of Finance, Nanjing Agricultural University, Nanjing 210095, China;
2. School of Economics and Management, Southeast University, Nanjing 211189, China;
3. MBA Education Center, Nanjing University of Finance and Economics, Nanjing 210023, China

Received:2018-05-30 Revised:2018-08-28 Online:2019-11-20 Published:2019-11-28

摘要/Abstract

摘要： 金融市场是一个复杂系统，银行之间不仅有直接的拆借关系，还能够通过投资市场建立间接关联。本文分析了资产内生相关性、资产降价出售以及银行投资行为等因素对银行间接关联程度的影响，基于这些因素通过持有共同资产构建银行系统的间接关联，并以此为基础通过平面极大过滤图方法生成银行间接关联网络，论证了该网络中的系统重要性银行，并通过对该网络结构特征的分析，发现间接关联网络具有小世界和无标度等特征，这些特征与银行通过直接拆借形成的网络相似。本文对于银行间接关联网络的研究不仅能够更加清晰地了解银行之间的关系，也为银行系统性风险的监管提供了新的视角。

关键词: 共同资产, 降价出售, 效用函数, 间接关联网络

Abstract: Financial market is a complex system, where banks not only connect with each other through direct lending, but also establish indirect correlationvia the investment market.A large number of researches have suggested that network resulted from interbank loans has some common topological properties. As shown in this paper, indirect correlation network between banks based on common assets is also worthy of discussion. The correlation between assets is established through fire sale and portfolios diversification, and then the indirect correlation between banks is constructed according to the portfolios chosen by risk aversion (CRRA) utility function.The influence of banks' investment behavior, endogenous correlation between assets and fire sale of common assets on the extent of indirect correlation between assets are tested respectively.Then the indirect correlation network between banks is set up with consideration of all the factors mentioned above and planar maximally filtered graph is used to filter redundant information. The importance of systemic important banks in the indirect correlation network is demonstrated. The small world phenomenon and scale-free phenomenon are also found by analyzing the indirect correlation network. On one hand, the observation in this paper makes the relationship between banks more clearly. On the other hand, a new perspective is also provided for regulators to promote the stability of banking system.

Key words: common assets, fire sale, utility function, indirect correlation network

中图分类号:

F830

王超, 何建敏, 马静. 基于共同持有资产的银行间接关联网络研究[J]. 中国管理科学, 2019, 27(11): 23-30.

WANG Chao, HE Jian-min, MA Jing. Indirect Correlation Network between Banks Based on Common Assets[J]. Chinese Journal of Management Science, 2019, 27(11): 23-30.

参考文献

[1] Caccioli F, Farmer J D, Foti N, et al. Overlapping portfolios, contagion, and financial stability[J]. Journal of Economic Dynamics and Control, 2015, 51:50-63.
[2] Glasserman P, Young H P. How likely is contagion in financial networks?[J]. Journal of Banking & Finance, 2015, 50:383-399.
[3] 吴宜勇, 胡日东, 袁正中. 共同资产持有的网络风险传染与政府救助[J]. 金融论坛, 2017,(8):35-45.
[4] 隋聪, 于洁晶, 宗计川. 银行间债务违约诱发资产减价出售——基于债务与资产关联的风险叠加传染研究[J]. 系统工程理论与实践, 2017, 37(11):2753-2764.
[5] Caccioli F, Shrestha M, Moore C, et al. Stability analysis of financial contagion due to overlapping portfolios[J]. Journal of Banking & Finance, 2014, 46:233-245.
[6] Greenwood R, Landier A, Thesmar D. Vulnerable banks[J]. Journal of Financial Economics, 2015, 115(3):471-485.
[7] Feinstein Z. Financial contagion and asset liquidation strategies[J]. Operations Research Letters, 2017, 45(2):109-114.
[8] Wagner W. Diversification at financial institutions and systemic crises[J]. Journal of Financial Intermediation, 2010, 19(3):373-386.
[9] May R M, Arinaminpathy N. Systemic risk:The dynamics of model banking systems[J]. Journal of the Royal Society Interface, 2010, 7(46):823-838.
[10] Beale N, Rand D G, Battey H, et al. Individual versus systemic risk and the regulator's dilemma[J]. Proceedings of the National Academy of Sciences, 2011, 108(31):12647-12652.
[11] Boss M, Elsinger H, Summer M, et al. Network topology of the interbank market[J]. Quantitative Finance, 2004, 4(6):677-684.
[12] Souma W, Fujiwara Y, Aoyama H. Complex networks and economics[J]. Physica A:Statistical Mechanics and its Applications, 2003, 324(1):396-401.
[13] Lublóy Á. Domino effect in the Hungarian interbank market[J]. Hungarian Economic Review, 2005, 52(4):377-401.
[14] Craig B, Von Peter G. Interbank tiering and money center banks[J]. Journal of Financial Intermediation, 2014, 23(3):322-347.
[15] 童中文. 银行间资产清算顺序优化与风险传染免疫机制[J]. 中国管理科学, 2012, 20(1):51-58.
[16] 邓超, 陈学军. 基于多主体建模分析的银行间网络系统性风险研究[J]. 中国管理科学, 2016, 24(1):67-75.
[17] 隋聪, 谭照林, 王宗尧. 基于网络视角的银行业系统性风险度量方法[J]. 中国管理科学, 2016, 24(5):54-64.
[18] Garlaschelli D, Battiston S, Castri M, et al. The scale-free topology of market investments[J]. Physica A:Statistical Mechanics and its Applications, 2005, 350(2-4):491-499.
[19] 樊瑛, 索丽娜, 沈晓松,等. 复杂网络视角下的NYSE市场投资结构特性研究[J]. 北京师范大学学报(自然科学版), 2008, 44(1):103-105.
[20] Battiston S, Rodrigues J F, Zeytinoglu H. The network of inter-regional direct investment stocks across Europe[J]. Advances in Complex Systems, 2007, 10(1):29-51.
[21] Masi G D. Bank-firms topology in Italy[J]. Empirical Economics, 2012, 43(2):851-866.
[22] Guo W, Minca A, Wang L. The topology of overlapping portfolio networks[J]. Statistics & Risk Modeling, 2016, 33(3-4):139-155.
[23] Cont R, Wagalath L. Running for the exit:Distressed selling and endogenous correlation in financial markets[J]. Mathematical Finance, 2013, 23(4):718-741.
[24] Cont R,Wagalath L. a. Fire sales forensics:Measuring endogenous risk[J]. Mathematical Finance, 2016, 26(4):835-866.
[25] 李华姣, 安海忠, 黄家宸,等. 基于节点拓扑特征的中国基金公司共持网络持股行为波动相关性[J]. 物理学报, 2014, 63(4):412-421.
[26] Tasca P, Mavrodiev P, Schweitzer F. Quantifying the impact of leveraging and diversification on systemic risk[J]. Journal of Financial Stability, 2014, 15:43-52.
[27] 曹小秋, 吴园园, 吴鹏昆. 基于网络的系统性风险测度方法及其在中国银行业的应用[J]. 数学的实践与认识, 2017, 47(4):83-93.
[28] Bouchaud J P, Cont R. A Langevin approach to stock market fluctuations and crashes[J]. European Physical Journal B, 1998, 6(4):543-550.
[29] Georg C P. The effect of the interbank network structure on contagion and common shocks[J]. Journal of Banking & Finance, 2013, 37(7):2216-2228.
[30] Watts D J, Strogatz S H. Collective dynamics of ‘small-world’ networks[J]. Nature, 1998, 393(6684):440.

基于共同持有资产的银行间接关联网络研究

Indirect Correlation Network between Banks Based on Common Assets

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 14

Metrics

本文评价

推荐阅读 10

[1]	李方超, 张成科, 朱怀念. Heston模型下DC型养老金等价管理费用问题研究[J]. 中国管理科学, 2019, 27(12): 11-21.
[2]	刘金荣, 徐琪. 全渠道零售下“Showrooms”对需求分布、定价和收益的影响研究[J]. 中国管理科学, 2019, 27(12): 88-99.
[3]	范丹丹, 徐琪, 程方正. 考虑退货影响的品牌商O2O渠道选择与决策优化[J]. 中国管理科学, 2019, 27(11): 138-148.
[4]	刘东霞, 陈红. 存在二手市场时耐用品垄断厂商再制造策略研究[J]. 中国管理科学, 2018, 26(6): 104-114.
[5]	陈义友, 张锦, 罗建强. 顾客选择行为对自提点选址的影响研究[J]. 中国管理科学, 2017, 25(5): 135-144.
[6]	孟凡生, 王雪松, 周亮亮. 双重成本控制标准作用下的员工激励模型研究[J]. 中国管理科学, 2014, 22(7): 94-99.
[7]	杨忠直, 孙皓辰, 彭俊伟. 基于财富效用的产权协商交易定价的计算求解和参数分析[J]. 中国管理科学, 2014, 22(2): 129-134.
[8]	姚海祥, 李仲飞. 基于非参数估计框架的期望效用最大化最优投资组合[J]. 中国管理科学, 2014, 22(1): 1-9.
[9]	解百臣, 杜纲. 效用型Malmquist指数方法及火电类上市公司实证分析[J]. 中国管理科学, 2010, 18(1): 46-51.
[10]	林志炳, 张岐山, 李美娟. 附免赔额保险协议下的供应链协调分析[J]. 中国管理科学, 2009, 17(6): 57-62.
[11]	姜树元, 姜青舫. 定常风险偏好效用函数式及其参数确定问题[J]. 中国管理科学, 2007, 15(1): 16-20.
[12]	王良, 杨乃定. 项目合作条件下基于资源的联盟成员效用模型及其求解[J]. 中国管理科学, 2005, (5): 100-104.
[13]	姜树元, 姜青舫. 消费者效用测度与产业需求函数[J]. 中国管理科学, 2004, (6): 81-85.
[14]	李必强, 刘运哲. 现代企业组织制度中的委托─代理关系[J]. 中国管理科学, 1999, (2): 57-61.