Abstract
Based on the existing financial system risk models, a set of time-lag financial system risk models is established considering the influence brought by time-lag factors on the financial risk system, and the dynamical behavior of this system is analyzed by using chaos theory. Through Matlab simulation, the bifurcation diagram and phase diagram of time-lag risk intensity and control intensity are plotted. The analysis shows that this kind of time-lag financial system risk model has complex dynamic behavior, different motion states will appear when different parameter values are selected, and the time-lag risk intensity parameter also has a very strong influence on the system motion. To ensure the operation of the financial system in a stable state, measures with certain delay effects must be taken to control the risk and to choose the appropriate time-lag control intensity, and too much or too little time-lag control intensity is not conducive to the benign operation of the system.
Highlights
Considering the possible lags of financial risks and regulatory measures, the article introduces a time-lag link based on the financial risk system model proposed by Xu Yuhua et al in 2016, proposes a time-lag financial system risk model, applies chaos theory in nonlinear dynamics to analyze the potential mechanism of financial system volatility, finds the best combination of parameters to ensure the smooth operation of this system model, and provides avoiding high-risk financial behaviors by providing some theoretical basis
Xu Yuhua et al proposed a circular structure financial risk system model that can contain three stages: the first stage is the destructive impact of external or internal shocks on the financial system; the second stage is the further damage to the stability of the financial system after the contagion effect among financial networks; the third stage is the financial institutions, regulatory system, and monetary policy in the face of systemic risk caused by the regulatory response [24], and the system model dynamics equation is as follows:
Z_ (c − 1)z − xy, where x is assumed to be the value of total systemic risk under the effect of external or internal shocks in the first stage, y is the value of total systemic risk under the effect of contagion in the second stage, and z denotes the value of systemic risk control in the third stage
Summary
Xu Yuhua et al proposed a circular structure financial risk system model that can contain three stages: the first stage is the destructive impact of external or internal shocks on the financial system; the second stage is the further damage to the stability of the financial system after the contagion effect among financial networks; the third stage is the financial institutions, regulatory system, and monetary policy in the face of systemic risk caused by the regulatory response [24], and the system model dynamics equation is as follows:. Z_(t) (c − 1)z(t) + fz(t − τ) − x(t)y(t), where x(t− τ) represents the value of systemic risk in period (t− τ) following shocks to the financial system from various factors and d represents the degree of risk of systemic risk in period (t− τ) in period t; y(t− τ) is the risk caused by systemic risk in period (t− τ) following contagion effects; and e represents its degree of risk remaining in period t; the risk control introduced in period (t− τ) may continue to have an impact in period t, and the parameter f represents its degree of control in period t and d, e, f ≥ 0. Compared with system (1), the system of time-lag differential equations can better reflect the time-lag effect of various risks in the financial system on the financial market, as well as the possible long-term impact of various risk controls on the financial system, so it can more realistically reflect the real financial system state and better reveal the dynamic behavior and characteristics of the system model. We select appropriate d, e, and f parameters to construct various nonlinear models of financial risk to analyze the long-term effects of each link on the financial system, taking into account the time-lagged nature of the effects of various links on the financial system risk
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
