General Electric Company

Michael Craig Clark

Kete Chalermkraivuth

Piero Patrone Bonissone

Naresh Sundaram Iyer

Rajesh Venkat Subbu

Srinivas Bollapragada

Richard Paul Messmer

Neil Holger White Eklund

Paul Venditti

Anindya Chakraborty

Thomas Paul Repoff

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.

Method and system for creating a dynamic systems based hybrid model for reasoning systems

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.

Methods and systems for analytical-based multifactor Multiobjective portfolio risk optimization

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.

Systems and methods for multi-objective portfolio optimization

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Glen Ellyn, IL, United States of America

Michael Craig Clark