The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 19, 2012

Filed:

Aug. 25, 2009
Applicants:

Leonid Merkoulovitch, Toronto, CA;

Yaacov Mutnikas, Toronto, CA;

Diane Reynolds, London, GB;

Dan Rosen, Toronto, CA;

Inventors:

Leonid Merkoulovitch, Toronto, CA;

Yaacov Mutnikas, Toronto, CA;

Diane Reynolds, London, GB;

Dan Rosen, Toronto, CA;

Assignee:

Algorithmics Software LLC, New York, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 40/00 (2012.01);
U.S. Cl.
CPC ...
Abstract

System, method and framework for generating scenarios used in risk management applications. The present invention is based on a generic framework that provides levels of abstraction, segregates risk factors and models, and structures a scenario generation process. In one aspect of the present invention, there is provided a framework for scenario generation for use in a risk management application, where the framework defines a plurality of components associated with a scenario set, where each component is represented by at least one of a set of data structures, and where the set of data structures comprises: at least one first data structure defining a group of risk factors with similar statistical properties; at least one second data structure defining the future distribution or evolutionary process of a risk factor in the group of risk factors; a third data structure defining a calibrated model for generating scenarios, where relationships between risk factors of the group of risk factors are defined therein, and where the calibrated model associates each second data structure with a first data structure; and a fourth data structure specifying how the first, second, and third data structures are to apply to a user-specified risk management problem.


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