A Minimal Agent-Based Model Reproduces the Overall Topology of Interbank Networks
Authored by Sara Cuenda, Maximiliano Fernandez, Javier Galeano, Jose A Capitan
Date Published: 2018
DOI: 10.18564/jasss.3562
Sponsors:
Spanish Ministry of Science and Innovation (MICINN)
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Abstract
The description of the empirical structure of interbank networks
constitutes an important field of study since network theory can be used
as a powerful tool to assess the resilience of financial systems and
their robustness against failures. On the other hand, the development of
reliable models of interbank market structure is relevant as they can be
used to analyze systemic risk in the absence of transaction data or to
test statistical hypotheses regarding network properties. Based on a
detailed data-driven analysis of bank positions (assets and liabilities)
taken from the Bankscope database, we here develop a minimal,
stochastic, agent-based network model that accounts for the basic
topology of interbank networks reported in the literature. The main
assumption of our model is that loans between banks attempt to
compensate assets and liabilities at each time step, and the model
renders networks comparable with those observed in empirical studies. In
particular, our model is able to qualitatively reproduce degree
distributions, the distribution of the number of transactions, the
distribution of exposures, the correlations with nearest-neighbor
out-degree, and the clustering coefficient. As our simple model captures
the overall structure of empirical networks, it can thus be used as a
null model for testing hypotheses relative to other specific properties
of interbank networks.
Tags
Complex networks
Agent-based modeling
Market
Systemic risk
Contagion
Food webs
Interbank markets
Intervality