| 英文摘要 |
Financial system dynamics are inherently complex, nonlinear and uncertain often characterized by the chaotic, random be¬havior and interactions. Understanding the complex financial-based dynamics within the society is crucial for designing effective economic policies to achieve sustainable economic goals, raise living standards and prosperity among Nations. This study addresses the nonlinear chaotic financial system (NCFS) model governed by the ordinary differential equations (ODEs), incorporates the three compartments related to loan interest rate, demand for capital investment and market inflation index. The investigation offers a comprehensive analysis of the system behavior by varying the NCFS model parameters and initial conditions of the state variables resulting into various cases and variants. The formulation of different case studies allows to examine system sensitivity as how the NCFS responds to changes in saving propensity, expenditure on investment, and sensitivity to price changes (market demand responsiveness). The complex NCFS dynamics are analyzed with the employment of four numerical solvers including Livermore solver, backward differentiation formula (BDF), explicit Runge-Kutta and implicit Runge-Kutta methods. The exploited numerical solvers prove to simulate accurate and efficient NCFS dynamics depicted by the comparative analysis among each numerical meth¬od. The efficiency of numerical solvers in generating the real-worl data system behavior for NCFS is evaluated by absolute error analysis. The detailed error analysis provides the insights that the error is minimum and close to zero for all the formulated NCFS cases and associated variants. The comprehensive analysis opens the path for practical implications in robust nonlinear modeling, numerical simulations and predicting complex financial systems. |
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