BIFURCATION AND CHAOTIC BEHAVIOR OF CREDIT RISK CONTAGION BASED ON FITZHUGH–NAGUMO SYSTEM

Abstract

This work introduces a FitzHugh–Nagumo (FHN) model of credit risk contagion based on the FHN system, which contains time-delay, Gaussian white noise, delayed feedback, weak periodic signal, and nonlinear resistance. The model depicts the dynamics behavior characteristics of evolution of credit risk contagion through simulation experiments. Meanwhile, numerical simulations show that, in a financial market, the dynamics system stability of credit risk contagion is positively related to the nonlinear resistance among participants of credit activities and to the inherent recovery capability attributed to the after-credit risk impact on economic subjects. However, the dynamics system stability of credit risk contagion is negatively related to the time-delay of credit risk contagion, the strength of Gaussian white noise, and the weak-signal cycle. Furthermore, the dynamics system of credit risk contagion introduces a series of Hopf bifurcation, inverse bifurcation and different degrees of chaotic oscillation phenomena with changes in these parameters.