公开(公告)号：US20120078814A1

公开(公告)日：2012-03-29

申请号：US13220115

申请日：2011-08-29

申请人： Andrew CLARK ,  Jeff Kenyon

发明人： Andrew CLARK ,  Jeff Kenyon

IPC分类号： G06Q40/06

CPC分类号： G06Q40/04 ,  G06Q40/06

摘要： The system and method described herein may be used to forecast realized volatility via wavelets and non-linear dynamics. In particular, a volatility time series that includes daily volatility values associated with a security may be decomposed into wavelets via multi-resolution analysis and dynamical properties associated with the individual wavelets may be analyzed to identify deterministic and non-deterministic wavelets and produce a volatility forecast derived from a fit computed on the deterministic wavelets. For example, the wavelets may be analyzed to discover time delay, Theiler, and embedding dimension values associated therewith, which may be used to project volatility values associated with each wavelet. The projected volatility values associated with each wavelet may then be summed to produce a volatility forecast associated with the security.

摘要翻译： 本文描述的系统和方法可用于通过小波和非线性动力学预测实现的波动性。 特别地，包括与安全性相关联的每日波动值的波动性时间序列可以通过多分辨率分析被分解为小波，并且可以分析与各个小波相关联的动力特性以识别确定性和非确定性小波并产生波动性预测 从确定性小波计算的拟合得出。 例如，可以分析小波以发现与之相关的时间延迟，Theiler和嵌入维度值，其可用于投影与每个小波相关联的波动率值。 然后可以将与每个小波相关联的预测波动率相加以产生与安全性相关联的波动性预测。

公开(公告)号：US08515850B2

公开(公告)日：2013-08-20

申请号：US13220115

申请日：2011-08-29

申请人： Andrew Clark ,  Jeff Kenyon

发明人： Andrew Clark ,  Jeff Kenyon

IPC分类号： G06Q40/00

CPC分类号： G06Q40/04 ,  G06Q40/06

摘要： The system and method described herein may be used to forecast realized volatility via wavelets and non-linear dynamics. In particular, a volatility time series that includes daily volatility values associated with a security may be decomposed into wavelets via multi-resolution analysis and dynamical properties associated with the individual wavelets may be analyzed to identify deterministic and non-deterministic wavelets and produce a volatility forecast derived from a fit computed on the deterministic wavelets. For example, the wavelets may be analyzed to discover time delay, Theiler, and embedding dimension values associated therewith, which may be used to project volatility values associated with each wavelet. The projected volatility values associated with each wavelet may then be summed to produce a volatility forecast associated with the security.

摘要翻译： 本文描述的系统和方法可用于通过小波和非线性动力学预测实现的波动性。 特别地，包括与安全性相关联的每日波动值的波动性时间序列可以通过多分辨率分析被分解为小波，并且可以分析与各个小波相关联的动力特性以识别确定性和非确定性小波并产生波动性预测 从确定性小波计算的拟合得出。 例如，可以分析小波以发现与之相关的时间延迟，Theiler和嵌入维度值，其可用于投影与每个小波相关联的波动率值。 然后可以将与每个小波相关联的预测波动率相加以产生与安全性相关联的波动性预测。

公开(公告)号：US20130024395A1

公开(公告)日：2013-01-24

申请号：US13189128

申请日：2011-07-22

申请人： Andrew Clark ,  Jeff Kenyon

发明人： Andrew Clark ,  Jeff Kenyon

IPC分类号： G06Q40/00 ,  G06N3/12

CPC分类号： G06Q40/06

摘要： The system and method described herein may be used to construct outperforming portfolios relative to target benchmarks. In particular, the system and method described herein may use multi-factor models that employ multi-objective evolutionary algorithms and mean variance optimization calculations to select constituents from a target benchmark index to include in a portfolio. The selected constituents may then be weighed to construct or rebalance the portfolio in a manner that can consistently outperform the target benchmark index while satisfying real-world constraints that relate to turnover limits, minimum and maximum stock positions, cardinalities, target market capitalizations, investment strategies, and other characteristics associated with the portfolio.

摘要翻译： 本文描述的系统和方法可用于构建相对于目标基准的表现优于投资组合。 特别地，本文描述的系统和方法可以使用采用多目标进化算法和均值方差优化计算的多因子模型，以从目标基准指数中选择要包括在投资组合中的成分。 所选择的成分可能被称重，以便能够持续优于目标基准指数的方式构建或重新平衡投资组合，同时满足与周转限制，最小和最大库存头寸，基数，目标市值，投资策略相关的现实世界约束 ，以及与投资组合相关的其他特征。