November 11, 2025Results in Control and OptimizationOpen Access

Fractal–fractional modeling and chaos analysis of a financial system with generalized memory kernels

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Authors

AAA. Agathiyan VBVinothkumar B AAAli Akgül

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Implication

This analysis assesses nonlinear dynamics and phase portraits in financial systems, implying fractional calculus can enhance understanding of system behavior.

Key Points

Nonlinear dynamics exhibit significant changes in response to variations in financial parameters, enhancing modeling accuracy.
Lyapunov exponent reveals critical chaotic transitions, demonstrating the effectiveness of advanced modeling techniques.
This approach utilizes a novel differential operator that successfully integrates fractal–fractional derivative operators in financial modeling.
Findings indicate memory effects and scaling critically influence financial system regime shifts and stability patterns.

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Agathiyan et al. (2025) studied this question.

synapsesocial.com/papers/69252e90c0ce034ddc355f9a https://doi.org/10.1016/j.rico.2025.100632

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Implication

This analysis assesses nonlinear dynamics and phase portraits in financial systems, implying fractional calculus can enhance understanding of system behavior.

Fractal–fractional modeling and chaos analysis of a financial system with generalized memory kernels

Discussion

Member takes

Implication

Key Points

Cite This Study

Fractal–fractional modeling and chaos analysis of a financial system with generalized memory kernels

Discussion

Member takes

Implication

Key Points

Cite This Study

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