主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院
论文

基于多主体建模分析的银行间网络系统性风险研究

展开
  • 1. 中南大学商学院, 湖南 长沙 410083;
    2. 中国人民银行郑州培训学院, 河南 郑州 450011

收稿日期: 2013-07-14

  修回日期: 2014-09-09

  网络出版日期: 2016-01-28

基金资助

国家自然科学基金资助项目(71173241);教育部新世纪人才基金(NCET-10-0830)

Studyon Multi-agent Models Analyses for Systemic Risk from the Interbank Network

Expand
  • 1. Business School of Central South University, Changsha 410083, China;
    2. Zhengzhou Training Institute, The People's Bank of China, Zhengzhou 450011, China

Received date: 2013-07-14

  Revised date: 2014-09-09

  Online published: 2016-01-28

摘要

本文基于多主体建模分析了银行间核心-边缘网络的系统性风险。模型假设银行通过最优投资组合配置,在流动性和资本约束前提下谋求利润最大化。通过建立银行间市场交易环境的仿真模型,依据银行行为决策动态形成资产负债表与银行间网络敞口的数据,评估金融监管政策在银行间市场的实施效应。同时,引入不同网络结构模型加以对比分析,发现尽管核心-边缘银行间网络体系比无标度网络更易遭受共同冲击和传染风险,但当处于金融困境时,在宏观审慎管理政策机制作用下,核心-边缘网络体系比其他结构网络表现出更强的恢复力特性。

本文引用格式

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 . DOI: 10.16381/j.cnki.issn1003-207x.2016.01.008

Abstract

In this paper a multi-agent model which analyses for systemic risk from the core-periphery structure in interbank network is proposed. Our model consists of a network of banks, which endogenously determine their optimal portfolio allocation by maximizing profits subject to liquidity and capital constraints. For the simulation framework to be useful for assessment of central bank policy, banking firm behavioral responses must be modelled in the context of interbank market conditions and with automated access to balance sheet and network exposure data to anchor the financial decisions being simulated. Different possible network structures are compared, while interbank markets network with the core-periphery topology is more susceptible to common shock and contagion than scale-free network, it tend to be more resilient to financial distress than others under macroprudential regulation and policy regime.

参考文献

[1] Allen F, Gale D. Financial contagion[J], Journal of Political Economy, 2000, 108(1):1-33.

[2] Freixas X, Parigi B M, Rochet J. Systemic risk, interbank relations and liquidity provision by the central bank[J]. Journal of Money, Credit and Banking, 2000, 32 (3), 611-638.

[3] Teteryatnikova M. Resilience of the interbank network to shocks and optimal bail-out strategy: Advantages of "tiered" banking systems[R]. Vienna Economics Papers 1203, University of Vienna, Department of Economics, 2012.

[4] Craig B, von Peter G. Interbank tiering and money center banks[R]. Journal of Financial Intermediation, 2014, 23(3):322-347.

[5] Finger K, D Fricke, T Lux. The italian interbank network:An overview[J]. In progress, Kiel Insitute for the World Economy, 2012.

[6] Finger K, T Lux. The evolution of the banking network:An actor-oriented approach[J]. In progress, Kiel Insitute for the World Economy, 2011.

[7] van Lelyveld I, in 't Veld D. Finding the core: Network structure in interbank markets[R]. Journal of Banking & Finance, 2014, 49:27-40.

[8] Peng Xingyun. Liquidity, liquidity excess and monetary policy [J]. Economic Research Journal, 2007, (11):55-70

[9] Pasche M. Interbank lending and the demand for central bank loans-A simple microfoundation[R]. Jena Economic Research Papers Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics, 2010.

[10] Pasche M. Fundamental uncertainty, portfolio choice, and liquidity preference theory[R]. Jena Economic Research Papers, Friedrich-Sehiuer-University Tena, Max-Planck-Institute of Econornics, 2009.

[11] Totzek, Alexander. The bank, the bank-run, and the central bank: The impact of early deposit withdrawals in a new Keynesian framework[R]. Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, 2008.

[12] Cifuentes R, Shin H S, Ferrucci G. Liquidity risk and contagion[J]. Journal of the European Economic Association, 2005, 3(2/3):556-566.

[13] Borgatti S P, Evertt M G. Models of core/periphery structures[J]. Social Networks, 2000, 21(4):375-395.

[14] Freeman L C. Centrality in social networks: conceptual clarification[J]. Social Network, 1979, 1(3):215-239.

[15] Wasserman S, Faust K. Social network analysis: Methods and applications[M]. Cambridge:Cambridge University Press, 1994.

[16] Yang Chaojun. Parameter uncertainty and investor's portfolio choice: Evidence from China stock market [J]. Chinese Journal of Management Science, 2008, 16(3):37-43.
文章导航

/