使用高斯混合模型对金融日志回报的基于的波动性分析.
1Department of Economics, Università degli Studi di Perugia, Via A. Pascoli 20, 06123 Perugia, Italy.
Entropy (Basel, Switzerland)
|November 27, 2024
概括
本研究引入了和高斯混合模型,以更好地评估金融市场波动性和风险. 这种方法比传统的方法提供了更强大的评估,假设对日志回报的正常分布.
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:
- 金融市场波动,即资产价格的波动,对于风险管理至关重要.
- 传统的波动性评估通常使用日志回报的标准偏差,假设高斯分布.
- 这种高斯假设在金融日志回报中经常无效,限制了准确性.
研究的目的:
- 探索 (微分) 的应用,以评估金融日志回报波动性.
- 开发一个更准确,更强大的金融风险评估框架.
- 整合先进的统计方法,以改善波动性和风险衡量计算.
主要方法:
- 使用 (微分) 来量化金融日志回报波动性.
- 使用高斯混合模型来估计日志回报的概率密度.
- 应用开发的框架来计算风险指标,如风险价值和预期缺口.
主要成果:
- 拟议的基于的方法为波动性评估提供了标准偏差的替代方案.
- 高斯混合模型有效地近似非高斯日志回报分布.
- 综合方法提高了金融风险指标的准确性.
结论:
- 与高斯混合模型相结合,为分析金融波动提供了一个卓越的框架.
- 这种方法解决了传统方法的局限性,因为它不假设高斯分布.
- 该研究为金融风险管理和决策提供了更坚实的基础.
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