在累积热谱中极端事件的签名
Ewa A Drzazga-Szczȩśniak1, Adam Z Kaczmarek2, Marta Kielak2
1Department of Physics, Faculty of Production Engineering and Materials Technology, Czestochowa University of Technology, 19 Armii Krajowej Ave., 42200 Czestochowa, Poland.
Entropy (Basel, Switzerland)
|April 26, 2025
概括
概率分布的累积效应会放大极端事件的发生. 基于香农的新信息度量,在杂的市场数据中量化这些极端事件.
科学领域:
- 定量金融是指数量金融.
- 信息理论是信息理论.
- 统计建模 统计建模
背景情况:
- 金融市场的极端事件带来了重大风险.
- 传统的统计方法可能难以识别极端事件的早期预警信号.
- 了解对概率分布的累积效应对于风险管理至关重要.
研究的目的:
- 确定经验概率分布的累积效应作为极端事件的驱动因素.
- 引入一种用于量化极端事件的新型信息措施.
- 用现实市场数据验证拟议的措施.
主要方法:
- 分析经验概率分布的累积效应.
- 开发一种信息测量方法,使用农对于联合概率.
- 用选择的市场数据验证案例研究,展示极端事件.
主要成果:
- 证实了概率分布的累积效应可以放大极端事件.
- 引入的信息措施有效量化了极端事件.
- 该测量仪检测到极端事件的独特特征,即使是在杂的数据集中.
结论:
- 拟议的信息措施显示了识别和量化极端事件的潜力.
- 调查结果表明,需要开发新的金融风险指标或分类器.
- 这项研究提供了一种新的方法来理解数据集中的极端事件放大.
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