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混合频率定量回归用于预测风险价值和预期缺口
Vincenzo Candila1, Giampiero M Gallo2, Lea Petrella3
1Department of Economics and Statistics, University of Salerno, Fisciano, Italy.
Annals of operations research
|June 26, 2023
概括
本研究引入了一种新的混合频率量子回归模型,用于估计金融风险指标,如风险值 (VaR) 和预期缺口 (ES). 该模型有效地整合了低频和高频数据,以改进风险评估.
科学领域:
- 量化金融 量化金融
- 计量经济学 计量经济学
背景情况:
- 量子回归是金融风险指标的标准.
- 现有的方法在混合频率数据方面面临挑战.
研究的目的:
- 开发一个混合频率的定量回归模型.
- 直接估计风险价值 (VaR) 和预期缺口 (ES).
主要方法:
- 纳入低频 (例如,每月) 和高频 (例如,每天) 变量.
- 导出每日回报的弱静态条件.
- 进行广泛的蒙特卡洛模拟.
主要成果:
- 拟议的模型有效地使用混合频率数据估计VaR和ES.
- 在后期测试中,与竞争型号相比,表现出优越的性能.
- 通过对能源商品 (原油,汽油期货) 的实证应用来验证.
结论:
- 新的混合频率量子回归提供了增强的风险测量能力.
- 优于现有的方法,特别是对于能源商品市场.
- 为金融风险分析提供了一个强大的框架,使用混合频率数据.
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