在具有复杂结构的模拟投资组合上使用高维共变矩阵估计器.
1Autonomous University of Baja California, Ensenada, Faculty of Sciences, 22860, Mexico.
Physical review. E
|March 19, 2025
概括
本研究介绍了高级的二步共差估计器,用于高维的投资组合分配. 这些方法改善了财务指标,为复杂的投资组合提供了新的风险管理策略.
科学领域:
- 量化金融 量化金融
- 统计建模 统计建模
- 复杂的系统复杂的系统.
背景情况:
- 高维共变矩阵结构对于投资组合分配至关重要.
- 现有的降噪方法在复杂的金融市场上存在局限性.
- 了解复杂的系统相互作用是强大的投资策略的关键.
研究的目的:
- 开发和评估用于投资组合分配的新型两步共差估计器.
- 为了比较层次嵌套,单因子和对角共差模型的性能.
- 评估降噪技术对财务绩效指标的影响.
主要方法:
- 利用随机矩阵理论,自由概率和确定性等效来减少噪音.
- 实施数据科学层次方法:两步共差估计器.
- 分析投资组合分配策略:最小差异和层次风险平价.
- 通过移动窗口和前进分析,将模拟结果与实证标准普尔500指数数据进行比较.
主要成果:
- 拟议的层次嵌套协差模型揭示了复杂的系统相互作用.
- 经验数据验证了复杂和单因素模型中观察到的风格化的投资组合事实.
- 两步估计器在分析的投资策略中显著提高了财务指标.
- 这些方法对具有高资产/日比率的场景显示出希望.
结论:
- 开发的两步协差估计器提供了更好的财务业绩.
- 层次模型捕捉了金融市场内部复杂的相互作用.
- 这些发现支持高维设置中的新风险管理和多样化方法.
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