Multiple stochastic and inverse stochastic resonances with transition phenomena in complex corporate financial systems

  • 0School of Finance, Yunnan University of Finance and Economics, Kunming 650221, People's Republic of China.

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Summary

This summary is machine-generated.

This study introduces a new model for complex corporate finance, demonstrating controllable stochastic resonance. The findings show how financial information variations can be used to manage resonance behaviors in financial systems.

Area Of Science

  • Financial Mathematics
  • Complex Systems Analysis
  • Economic Modeling

Background

  • Complex corporate financial systems are influenced by periodic information and exhibit stochastic resonance.
  • Understanding and controlling these phenomena are crucial for financial stability and predictability.

Purpose Of The Study

  • To propose a stochastic predator-prey complex corporate financial system model driven by periodic information.
  • To introduce signal power amplification for quantifying stochastic resonance and develop analysis methods.
  • To investigate the controllable analysis of stochastic resonance in financial predator-prey dynamics.

Main Methods

  • Development of a stochastic predator-prey complex corporate financial system model.
  • Introduction of signal power amplification for quantifying stochastic resonance.
  • Optimization of a simplified integral calculation method for model enhancement.
  • Stochastic simulations and numerical calculations to observe resonance phenomena.

Main Results

  • Observation of multiple stochastic resonance and multiple inverse stochastic resonance phenomena.
  • Demonstration that initial financial information, periodic information frequency, and corporate growth capacity induce these resonances.
  • Identification of state transitions between stochastic and inverse stochastic resonance behaviors.

Conclusions

  • The proposed model offers superior performance over benchmark models.
  • Findings suggest the potential for regulating and controlling stochastic and inverse stochastic resonance in complex corporate finance.
  • Controllable stochastic resonance behaviors can be achieved through parameter manipulation.

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