The global financial crisis in 2007-2009 demonstrated that systemic risk can spread all over the world through a complex web of financial linkages  . In particular, interbank credit networks shape the core of the financial system, in which  interconnected risk emerges from a massive number of temporal transactions between banks. However, the lack of fundamental knowledge about the dynamic nature of interbank networks makes it difficult to evaluate and control systemic risk. Here, we analyze the dynamics of real interbank networks at a daily temporal resolution. While daily networks have been flexibly changing their structure from day to day, entailing entries and exits of banks, we discover explicit dynamical patterns that have been surprisingly stable over time even amid the global financial crisis. The emergence of these dynamical patterns is accurately reproduced by a model, in which banks' demand for trading follows a random walk . The discovery of fundamental patterns in the daily evolution of interbank networks will enhance our ability to evaluate systemic risk and could contribute to the dynamic management of financial stability.
The global financial crisis in 2007-2009 demonstrated that systemic risk can spread all over the world through a complex web of financial linkages , yet we still lack fundamental knowledge about the evolution of the financial web . In particular, interbank credit networks shape the core of the financial system, in which a time-varying interconnected risk emerges from a massive number of temporal transactions between banks. The current lack of understanding of the mechanics of interbank networks makes it difficult to evaluate and control systemic risk. Here, we uncover fundamental dynamics of interbank networks by seeking the patterns of daily transactions between individual banks. We find stable interaction patterns between banks from which distinctive network-scale dynamics emerge. In fact, the dynamical patterns discovered at the local and network scales share common characteristics with social communication patterns of humans. To explain the origin of "social" dynamics in interbank networks, we provide a simple model that allows us to generate a sequence of synthetic daily networks characterized by the observed dynamical properties . The discovery of dynamical principles at the daily resolution will enhance our ability to assess systemic risk and could contribute to the real-time management of financial stability.
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, yet we still lack fundamental knowledge about the evolution of the financial web
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a time-varying
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However, the lack of fundamental knowledge about the dynamic nature
The current lack of understanding of the mechanics
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analyze the dynamics of real interbank networks at a daily temporal resolution. While daily networks have been flexibly changing their structure from day to day, entailing entries and exits of banks, we discover explicit dynamical patterns that have been surprisingly stable over time even amid the global financial crisis. The emergence of these dynamical patterns is accurately reproduced by a model, in which banks' demand for trading follows a random walk
uncover fundamental dynamics of interbank networks by seeking the patterns of daily transactions between individual banks. We find stable interaction patterns between banks from which distinctive network-scale dynamics emerge. In fact, the dynamical patterns discovered at the local and network scales share common characteristics with social communication patterns of humans. To explain the origin of "social" dynamics in interbank networks, we provide a simple model that allows us to generate a sequence of synthetic daily networks characterized by the observed dynamical properties
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fundamental patterns in the daily evolution of interbank networks
dynamical principles at the daily resolution
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evaluate
assess
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dynamic
real-time