多个随机和反随机共振与复杂的企业金融系统中的过渡现象
Guangyan Zhong1, Jiang-Cheng Li1
1School of Finance, Yunnan University of Finance and Economics, Kunming 650221, People's Republic of China.
Chaos (Woodbury, N.Y.)
|June 5, 2024
概括
这项研究引入了复杂的企业金融的新模型,展示了可控制的随机共振. 研究结果表明,如何利用财务信息的变化来管理金融系统中的共振行为.
科学领域:
- 金融数学 金融数学
- 复杂系统分析 复杂系统分析
- 经济建模经济建模
背景情况:
- 复杂的企业金融系统受到周期性信息的影响,并表现出随机共振.
- 了解和控制这些现象对于金融稳定和可预测性至关重要.
研究的目的:
- 提出一个由周期性信息驱动的随机捕食者-猎物复杂的企业金融系统模型.
- 为量化随机共振引入信号功率放大,并开发分析方法.
- 研究金融掠食者-猎物动态中随机共振的可控分析.
主要方法:
- 开发一个随机捕食者-猎物复杂的企业金融系统模型.
- 引入信号功率放大用于量化随机共振.
- 为模型增强优化简化积分计算方法的优化.
- 随机模拟和数值计算来观察共振现象.
主要成果:
- 观察多个随机共振和多个逆随机共振现象.
- 证明初始财务信息,定期信息频率和企业增长能力会引起这些共.
- 在随机和逆随机共振行为之间的状态过渡的识别.
结论:
- 拟议的模型比基准模型提供了更高的性能.
- 研究结果表明,在复杂的企业金融中,有能力调节和控制随机和逆随机共振.
- 可控制的随机共振行为可以通过参数操纵来实现.
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