The interbank network is convenient for liquidity adjustment of the interbank market.But, the network configuration also increases risk contagion among the interbank market.However, the relationship between the network configuration and the systemic risk is a disputable issue in the research area.On one hand, the systemic risk is a typical small probability event which only happens in extreme circumstance.On the other hand, simulated interbank market network in the research area is different from real interbank market configuration.So building a realistic network model and researching the behavior of real network model in extreme circumstance are the key issues.Based on reality interbank network model, two evaluation parameters of the systemic risk: VaR and ES are presented in this paper.Firstly, Monte Carlo method is utilized to simulate the external impact of interbank system.Then, the systemic risk VaR and ES which can reflect the small probability characters of the systemic risk are estimated and the tail properties of interbank system loss are captured.Secondly, real bank parameters are utilized to calibrate three kinds of interbank network in simulation.Such a method ensures the reality and reliability of simulation results.Finally, three valuable conclusions are drawn: (1) External impact will trigger contagion.The interbank system loss will change from norm distribution to heavy tail distribution and then to bimodal distribution.(2) The contagion probability of high density interbank network is smaller than that of low density network, but the destruction is much higher.(3) The potential contagion will enlarge the systemic risk and default contagion effect will increase exponentially.A model which can evaluate the extent of the destruction of the systemic risk in extreme condition is presented.Furthermore, the simulation results comprehensively reveal the relationship between the network configuration and the systemic risk.
SUI Cong, TAN Zhao-lin, WANG Zong-yao
. A Network Perspective Measurement Method for Banking Systemic Risk[J]. Chinese Journal of Management Science, 2016
, 24(5)
: 54
-64
.
DOI: 10.16381/j.cnki.issn1003-207x.2016.05.007
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