Credit Contagion in Financial Markets: A Network-Based Approach

M Steinbacher , F Black , N Kiyotaki , F Schweitzer , R C Merton , D W Diamond , B Craig , C P Kindleberger , D Duffie , G Iori , C M Reinhart , D J Watts , R Cifuentes , R A Jarrow , P Gai , S Wasserman , E Nier , S Battiston , M E Newman , F Allen , A Shleifer , M K Brunnermeier , Matej Steinbacher , S Gilchrist , A Shleifer , I Van Lelyveld , O Vasicek , E I Altman , A G Haldane , G Iori , Y Leitner , R Albert , P Gai , X Huang , H Markowitz , D Egloff , N Beale , D Acemoglu , M Steinbacher , H Degryse , V V Acharya , L Tesfatsion , C Upper , Mitja Steinbacher , R Pastor-Satorras , C Upper , M Boss , M O Jackson , Matjaz Steinbacher , F Allen , V V Acharya , D Fricke , C H Furfine , A Dasgupta

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2012

We propose a network-based model of credit contagion and examine the e�ects of idiosyncratic and systemic shocks to individual banks and the banking system. The banking system is built as a network in which banks are connected to each other through the interbank market. The microstructure captures the relation between debtors and creditors, and the macroeconomic events capture the sensitivity of the banks' �nancial strenght to macroeconomic events, such as housing. We have demonstrated that while idiosyncratic shocks do not have a potential to substantially disturb the banking system, macroeconomic events of higher magnitudes could be highly harmful, especially if they also spur contagion. In a concerted default of more banks, the stability of a banking system tends to decrease disproportionately. In addition, credit risk analysis is highly sensitive to the network topology and exhibits a nonlinear characteristic. Capital ratio and recovery rates are two additional factors that contribute to the stability of the �nancial system