Abstract

This paper proposes a model of the dynamics of credit contagion through non-performing loans on financial networks. Credit risk contagion is modeled in the context of the classical SIS (Susceptibles-Infected-Susceptibles) epidemic processes on networks but with a fundamental novelty. In fact, we assume the presence of two different classes of infected agents, and then we differentiate the dynamics of assets subject to idiosyncratic risk from those affected by systemic risk by adopting a SIIS (Susceptible-Infected1-Infected2-Susceptible) model. In the recent literature in this field, the effect of systemic credit risk on the performance of the financial network is a hot topic. We perform numerical simulations intended to explore the roles played by two different network structures on the long-term behavior of assets affected by systemic risk in order to analyze the effect of the topology of the underlying network structure on the spreading of systemic risk on the structure. Random graphs, i.e., the Erdös–Rényi model, are considered “benchmark” network structures while core-periphery structures are often indicated in the literature as idealized structures, although they are able to capture interesting, specific features of real-world financial networks. Moreover, as a matter of comparison, we also perform numerical experiments on small-world networks.

Highlights

  • Network modeling in social and economic processes, either analytical- or simulation-based, has demonstrated its importance in scientific literature produced in the last two decades, and the analysis of the emergence of complex and heterogeneous connectivity patterns in many sociotechnical systems has been a hot topic in recent years

  • We extend the classical approach by dividing the population for each node into three classes: susceptibles S, i.e., those that may be infected by credit risk, infectious1 I1, and infectious2 I2

  • We evaluate the dynamics of the mean value of assets subject to systemic risk on the network whose graphical representation is provided on the right-hand side of each figure

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Summary

Introduction

Network modeling in social and economic processes, either analytical- or simulation-based, has demonstrated its importance in scientific literature produced in the last two decades (see [1,2] for a general review of related theory, methods, and applications), and the analysis of the emergence of complex and heterogeneous connectivity patterns in many sociotechnical systems has been a hot topic in recent years (see [3] and references therein). Techniques coming from network theory have been applied in recent years to model the financial systemic risk correlated with the phenomenon of contagion These techniques have shown interesting potential in assessing key features of dynamics, Mathematics 2019, 7, 713; doi:10.3390/math7080713 www.mdpi.com/journal/mathematics. We explore the contagion dynamics over different networks’ architectures with the main goal being to understand the impact of the network structure on the systematic part and on the idiosyncratic part of the risk in the Vasicek loan portfolio value model. The spreading of risk in the network is modeled in the framework of epidemic processes in complex networks [3] with the novelty, with respect to other models in the related literature, of having split credits between a group subject to systemic risk and another subject to idiosyncratic risk, following the Vasicek model. A short section of concluding remarks closes the paper

Credit Risk
Probability Density Function of Credit Losses
Systemic and Idiosyncratic Risk in the Vasicek Loan Portfolio Value Model
Dynamics of Credit Risk Contagion
Credit Risk Contagion on Networks
Numerical Experiments
Findings
Conclusions and Research Perspectives
Full Text
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