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Credit Risk Contagion and Systemic Risk on Networks

Author

Listed:
  • Marina Dolfin

    (Department of Engineering, University of Messina, 98166 Messina, Italy
    These authors contributed equally to this work.)

  • Damian Knopoff

    (CIEM CONICET and FaMAF—National University of Córdoba, Córdoba CP:X5000HUA, Argentina
    These authors contributed equally to this work.)

  • Michele Limosani

    (Department of Economics, University of Messina, 98122 Messina, Italy
    These authors contributed equally to this work.)

  • Maria Gabriella Xibilia

    (Department of Engineering, University of Messina, 98166 Messina, Italy
    These authors contributed equally to this work.)

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.

Suggested Citation

  • Marina Dolfin & Damian Knopoff & Michele Limosani & Maria Gabriella Xibilia, 2019. "Credit Risk Contagion and Systemic Risk on Networks," Mathematics, MDPI, vol. 7(8), pages 1-16, August.
  • Handle: RePEc:gam:jmathe:v:7:y:2019:i:8:p:713-:d:255390
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    References listed on IDEAS

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    3. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. Berloco, Claudia & Argiento, Raffaele & Montagna, Silvia, 2023. "Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1065-1077.
    5. Huang, Qi-An & Zhao, Jun-Chan & Wu, Xiao-Qun, 2022. "Financial risk propagation between Chinese and American stock markets based on multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    6. Dong Wang & Yi Zhao & Hui Leng, 2020. "Dynamics of Epidemic Spreading in the Group-Based Multilayer Networks," Mathematics, MDPI, vol. 8(11), pages 1-15, October.

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