复杂的功能结构的非参数预测性缺陷回归
Mohammed B Alamari1, Fatimah A Almulhim2, Zoulikha Kaid1
1Department of Mathematics, College of Science, King Khalid University, Abha 62529, Saudi Arabia.
Entropy (Basel, Switzerland)
|September 27, 2024
概括
本研究引入了一种新的有条件预期缺口风险指标,使用预期. 这种新的方法为金融风险管理提供了一种实用而敏感的工具,其性能优于标准方法.
科学领域:
- 量化金融 量化金融
- 金融风险管理 金融风险管理
- 统计建模 统计建模
背景情况:
- 传统的风险管理指标,如风险价值 (VaR),在捕捉尾部风险方面存在局限性.
- 条件预期缺口 (CES) 是一个更全面的风险指标,但其估计可能是复杂的.
- 在金融时间序列分析中,需要强大且易于实施的风险指标.
研究的目的:
- 为加强风险管理引入新的有条件预期缺口 (CES) 功能.
- 为这个新的CES指标开发一个非参数估计器.
- 使用财务数据证明新风险指标的实际适用性和敏感性.
主要方法:
- 定义一个新的CES函数,使用expectiles作为缺口值.
- 使用Nadaraya-Watson方法构建一个非参数估计器.
- 使用功能时间序列分析和度不等式来确定非对称性质.
- 通过真实和模拟的金融时间序列数据进行验证.
主要成果:
- 开发了一种新型的非参数CES估计器,并确定其趋同率.
- 新的风险指标表现出易于实施和对金融时间序列波动的敏感性.
- 经验研究证实了拟议的风险工具的可行性.
- 对比分析显示,与标准的缺口措施相比,有优势.
结论:
- 拟议的基于预期的CES函数在金融风险管理方面提供了有价值和实际的进步.
- 非参数估计器在统计学上是合理的,并且在真实世界的金融数据上表现良好.
- 与传统方法相比,这种新指标提供了更细致的风险理解.
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