A Compartmental Model for Financial Systemic Risk: Extending an SIRS Model to Capture Mitigation and Protection Dynamics
نویسندگان
1 Department of Mathematics and Computer Science, School of Natural Sciences, Great Zimbabwe University, Masvingo, Zimbabwe
2 Department of Mathematics and Computer Science, School of Natural Sciences, Great Zimbabwe University, Masvingo, Zimbabwe
3 Department of Mathematics and Applied Mathematics, Faculty of Science, Pretoria, South Africa and Institute of Research and Professional Training, Emirates Aviation University, Dubai International Academic City, UAE
doi
10.22052/mir.2025.256837.1520چکیده
Financial systemic risk refers to the transmission of distress among financial institutions, posing a significant threat to economic stability. Inspired by epidemiological modelling, this study develops an extended compartmental framework based on the classical SIRS model to analyse the spread and control of financial systemic risk within a banking network. The model introduces six compartments: susceptible, immune, infected, curated, mitigated, and removed to capture the diverse states of banks under systemic stress and regulatory intervention. Central bank actions such as curatorship, mitigation, and temporary protection are explicitly incorporated. The model is formulated as a system of ordinary differential equations, and analytical techniques are employed to derive the risk reproduction number, $R_{sr}$, which serves as a threshold parameter governing the system’s long-term behaviour. Two equilibrium points are identified: the risk-free equilibrium, which is locally and globally asymptotically stable when $R_{sr} < 1$, and the endemic equilibrium, which persists when $R_{sr} > 1$. Numerical simulations demonstrate how variations in key parameters such as the rate of curatorship, mitigation, and protection affect the prevalence of financial contagion. While the model does not yield fundamentally new theoretical insights, it offers a structured framework for evaluating the impact of regulatory interventions. The findings underscore the utility of epidemiological modelling in financial risk analysis and highlight the importance of timely and targeted control measures to prevent cascading failures in the banking sector.