全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
Finance  2020 

境内银行网络结构的特征分析
Analysis of the Characteristics of the Network Structure of Domestic Banks in China

DOI: 10.12677/FIN.2020.103019, PP. 188-199

Keywords: 境内银行,复杂网络,拓扑网络特征,小世界网络
Domestic Bank
, Complex Network, Topological Network Features, Small World Network

Full-Text   Cite this paper   Add to My Lib

Abstract:

本文基于12家我国境内银行2013年至2017年资产负债表中的同业拆借数据,采用复杂网络理论、阈值法对其构成的银行同业拆借网络的节点度、平均路径长度以及聚集系数等拓扑特征进行研究分析,并通过其分析结果进而推断出我国境内银行网络的特性。实证结果发现,我国境内银行的同业拆借网络有着节点度大、平均路径长度小且聚集系数高的特点,呈现小世界特征,一方面表明我国境内银行网络的同业拆借市场效率高、分布广,网络中的银行可以较快较便捷地获得融资,市场也有着高度合理的资源配置;另一方面表明我国境内银行网络有着较高的风险传染性,容易牵一发而动全身,轻则导致整个银行网络的瘫痪,重则引发全国性的金融危机。
Based on the inter-bank lending data of 12 domestic banks from 2013 to 2017, this paper uses the complex network theory and threshold method to analyze the topological characteristics of the inter-bank lending network, such as node degree, average path length and aggregation coefficient, and then infers the characteristics of the domestic bank network through its analysis results. The empirical results show that the inter-bank lending network of domestic banks in China has the characteristics of large node degree, small average path length and high aggregation coefficient, showing the characteristics of a small world. On the one hand, it shows that the inter-bank lending market of domestic banks in China has high efficiency and wide distribution, the banks in the network can obtain financing quickly and conveniently, and the market also has a highly reasonable resource allocation. On the one hand, it shows that the banking network in China has a high risk contagion, which is easy to lead to the whole body, light will lead to the paralysis of the whole banking network, and heavy will lead to the national financial crisis.

References

[1]  左振宇, 李守伟, 何建敏. 我国银行网络拓扑结构特征的实证研究[J]. 华东经济管理, 2012, 26(2): 98-101.
[2]  Soram?ki, K., Bech, M.L., Arnold, J., et al. (2006) The Topology of Interbank Payment Flows. Physica: A Sta-tistical Mechanics & Its Applications, 379, 317-333.
https://doi.org/10.1016/j.physa.2006.11.093
[3]  De Masi, G. and Gallegati, M. (2007) Bank-Firms Topology in Italy. Empirical Economics, 43, 1-16.
https://doi.org/10.1007/s00181-011-0512-x
[4]  汪贵浦, 余雷鸣, 陈明亮, 周清. 商业银行空间市场力的演进规律——中国光大银行拓扑结构的分析[J]. 地理科学, 2015, 35(3): 275-282.
[5]  牛晓健, 吕潇潇. 中国银行间同业拆借市场网络系统的研究——基于复杂网络方法的探索[J]. 盐城工学院学报(社会科学版), 2016, 29(4): 32-38.
[6]  陈少炜, 李旸. 我国银行体系的网络结构特征——基于复杂网络的实证分析[J]. 经济问题, 2016(8): 56-63.
https://doi.org/10.1007/s35128-016-0145-z
[7]  隋新, 何建敏, 李守伟. 嵌入银企间和企业间市场的内生信贷网络模型构建[J]. 北京理工大学学报(社会科学版), 2017, 19(3): 99-107.
[8]  Aldasoro, I. and Alves, I. (2016) Multiplex In-terbank Networks and Systemic Importance: An Application to European Data. Journal of Financial Stability, 35, 17-37.
https://doi.org/10.1016/j.jfs.2016.12.008
[9]  黄玮强, 范铭杰, 庄新田. 基于借贷关联网络的我国银行间市场风险传染[J]. 系统管理学报, 2019(5): 898-906.
[10]  Albert, R. and Barabási, A.L. (2002) Statistical Mechanics of Complex Networks. Reviews of Modern Physics, 26, 47-97.
https://doi.org/10.1103/RevModPhys.74.47
[11]  李茂. 中国产业关联网络的拓扑特征演变[J]. 技术经济, 2016, 35(7): 80-89.
[12]  Watts, D., Strogatz, J. and Steven, H. (1998) Collective Dynamics of “Small-World” Networks. Nature, 393, 440-442.
https://doi.org/10.1038/30918

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133