公开(公告)号：US08533147B2

公开(公告)日：2013-09-10

申请号：US12971332

申请日：2010-12-17

申请人： Paul Venditti ,  Thomas Paul Repoff ,  Michael Craig Clark

发明人： Paul Venditti ,  Thomas Paul Repoff ,  Michael Craig Clark

IPC分类号： G06F17/00 ,  G06N7/00

CPC分类号： G06N5/04

摘要： A method for creating a dynamic systems based hybrid model for reasoning systems is described. The method receives, at a server, a plurality of expert identified deal attributes. The method presents a conjoint analysis questionnaire for input by one or more respondents. The conjoint analysis questionnaire includes questions based on the plurality of expert identified deal attributes. The method receives responses of the one or more respondents to the conjoint analysis questionnaire. The method then defines an expert reasoning model based on the responses of the one or more respondents to the conjoint analysis questionnaire. The method accesses historical deal information of one or more deals, the historical deal information including one or more deals, each deal including a plurality of expert identified deal attributes and a part-worth associated with each of the deal attributes. Finally, the method validates the expert reasoning model based on the historical deal information.

摘要翻译： 描述了一种用于为推理系统创建基于动态系统的混合模型的方法。 该方法在服务器处接收多个专家识别的交易属性。 该方法提供了一个或多个受访者输入的联合分析问卷。 联合分析问卷包括基于多个专家识别的交易属性的问题。 该方法接收一个或多个受访者对联合分析问卷的回复。 然后，该方法基于一个或多个受访者对联合分析问卷的响应来定义专家推理模型。 该方法访问一个或多个交易的历史交易信息，历史交易信息包括一个或多个交易，每个交易包括多个专家识别交易属性和与每个交易属性相关联的零件价值。 最后，该方法根据历史交易信息验证了专家推理模型。

公开(公告)号：US07640201B2

公开(公告)日：2009-12-29

申请号：US10390710

申请日：2003-03-19

申请人： Kete Charles Chalermkraivuth ,  Anindya Chakraborty ,  Michael Craig Clark ,  Richard Paul Messmer

发明人： Kete Charles Chalermkraivuth ,  Anindya Chakraborty ,  Michael Craig Clark ,  Richard Paul Messmer

IPC分类号： G06Q99/00

CPC分类号： G06Q40/06

摘要： The invention provides systems and methods for determining the allocation of securities in a portfolio. The method includes providing a collection of securities in a portfolio, each security being associated with associated attributes; providing risk factor data related to the portfolio; pooling the securities into a plurality of security clusters based on the attributes associated with each security and the risk factor data, each security being assigned to an security cluster, the pooling being performed using multivariate decision tree processing; processing the security clusters using a nonlinear programming optimizer to generate optimization results; and presenting the optimization results in a risk-return space for determination of a security allocation.

摘要翻译： 本发明提供用于确定投资组合中证券分配的系统和方法。 该方法包括在投资组合中提供证券集合，每个证券与相关联的属性相关联; 提供与投资组合相关的风险因素数据; 基于与每个安全性相关联的属性和风险因子数据将证券集中到多个安全集群中，每个安全性被分配给安全集群，所述集合使用多变量决策树处理来执行; 使用非线性编程优化器处理安全集群以生成优化结果; 并将优化结果呈现在用于确定安全分配的风险回报空间中。

公开(公告)号：US20120158640A1

公开(公告)日：2012-06-21

申请号：US12971332

申请日：2010-12-17

申请人： Paul Venditti ,  Thomas Paul Repoff ,  Michael Craig Clark

发明人： Paul Venditti ,  Thomas Paul Repoff ,  Michael Craig Clark

IPC分类号： G06N5/02

CPC分类号： G06N5/04

摘要： A method for creating a dynamic systems based hybrid model for reasoning systems is described. The method receives, at a server, a plurality of expert identified deal attributes. The method presents a conjoint analysis questionnaire for input by one or more respondents. The conjoint analysis questionnaire includes questions based on the plurality of expert identified deal attributes. The method receives responses of the one or more respondents to the conjoint analysis questionnaire. The method then defines an expert reasoning model based on the responses of the one or more respondents to the conjoint analysis questionnaire. The method accesses historical deal information of one or more deals, the historical deal information including one or more deals, each deal including a plurality of expert identified deal attributes and a part-worth associated with each of the deal attributes. Finally, the method validates the expert reasoning model based on the historical deal information.

摘要翻译： 描述了一种用于为推理系统创建基于动态系统的混合模型的方法。 该方法在服务器处接收多个专家识别的交易属性。 该方法提供了一个或多个受访者输入的联合分析问卷。 联合分析问卷包括基于多个专家识别的交易属性的问题。 该方法接收一个或多个受访者对联合分析问卷的回复。 然后，该方法基于一个或多个受访者对联合分析问卷的响应来定义专家推理模型。 该方法访问一个或多个交易的历史交易信息，历史交易信息包括一个或多个交易，每个交易包括多个专家识别交易属性和与每个交易属性相关联的零件价值。 最后，该方法根据历史交易信息验证了专家推理模型。

公开(公告)号：US07542932B2

公开(公告)日：2009-06-02

申请号：US10781780

申请日：2004-02-20

申请人： Kete Charles Chalermkraivuth ,  Srinivas Bollapragada ,  Piero Patrone Bonissone ,  Michael Craig Clark ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

发明人： Kete Charles Chalermkraivuth ,  Srinivas Bollapragada ,  Piero Patrone Bonissone ,  Michael Craig Clark ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

IPC分类号： G06Q40/00

CPC分类号： G06Q40/00 ,  G06Q10/06375 ,  G06Q40/06

摘要： The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: generating an initial population of solutions of portfolio allocations; performing a first multi-objective process, based on the initial population and the competing objectives, to generate a first interim efficient frontier; performing a second multi-objective process, based on the initial population and the competing objectives, to generate a second interim efficient frontier; and fusing the first interim efficient frontier with the second interim efficient frontier to create an augmented efficient frontier for use in investment decisioning.

摘要翻译： 本发明的系统和方法针对组合优化和相关技术。 例如，本发明提供了一种用于基于竞争目标和构成组合问题的多个约束的投资决策中的多目标投资组合优化的方法，所述方法包括：生成投资组合分配的最初解决方案群体; 根据初始人口和竞争目标，进行第一个多目标过程，以产生第一个临时有效的前沿; 根据初始人口和竞争目标进行第二个多目标过程，以产生第二个临时有效的边界; 并将第一个临时有效的边界与第二个临时有效的前沿融合，创造出一个扩大的投资决策的有效前沿。

公开(公告)号：US20050187844A1

公开(公告)日：2005-08-25

申请号：US10781780

申请日：2004-02-20

申请人： Kete Charles Chalermkraivuth ,  Srinivas Bollapragada ,  Piero Patrone Bonissone ,  Michael Craig Clark ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

发明人： Kete Charles Chalermkraivuth ,  Srinivas Bollapragada ,  Piero Patrone Bonissone ,  Michael Craig Clark ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

IPC分类号： G06Q40/00 ,  G06F17/60

CPC分类号： G06Q40/00 ,  G06Q10/06375 ,  G06Q40/06

摘要： The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: generating an initial population of solutions of portfolio allocations; performing a first multi-objective process, based on the initial population and the competing objectives, to generate a first interim efficient frontier; performing a second multi-objective process, based on the initial population and the competing objectives, to generate a second interim efficient frontier; and fusing the first interim efficient frontier with the second interim efficient frontier to create an augmented efficient frontier for use in investment decisioning.

摘要翻译： 本发明的系统和方法针对组合优化和相关技术。 例如，本发明提供了一种用于基于竞争目标和构成组合问题的多个约束的投资决策中的多目标投资组合优化的方法，所述方法包括：生成投资组合分配的最初解决方案群体; 根据初始人口和竞争目标，进行第一个多目标过程，以产生第一个临时有效的前沿; 根据初始人口和竞争目标进行第二个多目标过程，以产生第二个临时有效的边界; 并将第一个临时有效的边界与第二个临时有效的前沿融合，创造出一个扩大的投资决策的有效前沿。