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.
Patent No.:
Date of Patent:
Apr. 16, 2013
Filed:
Jan. 06, 2012
Jie Chen, Chappaqua, NY (US);
Timothy John Breault, Huntersville, NC (US);
Fernando Cela Diaz, New York, NY (US);
William Anthony Nobili, Charlotte, NC (US);
Sandi Setiawan, Charlottle, NC (US);
Harsh Singhal, Charlotte, NC (US);
Agus Sudjianto, Charlotte, NC (US);
Andrea Renee Turner, Rock Hill, SC (US);
Bradford Timothy Winkelman, Wilmington, DE (US);
Jie Chen, Chappaqua, NY (US);
Timothy John Breault, Huntersville, NC (US);
Fernando Cela Diaz, New York, NY (US);
William Anthony Nobili, Charlotte, NC (US);
Sandi Setiawan, Charlottle, NC (US);
Harsh Singhal, Charlotte, NC (US);
Agus Sudjianto, Charlotte, NC (US);
Andrea Renee Turner, Rock Hill, SC (US);
Bradford Timothy Winkelman, Wilmington, DE (US);
Bank of America Corporation, Charlotte, NC (US);
Abstract
Embodiments of the present invention relate to methods and apparatuses for determining leading indicators and/or for modeling one or more time series. For example, in some embodiments, a method is provided that includes: (a) receiving first data indicating the value of a total income amount for a plurality of consumers over a period of time; (b) receiving second data indicating the value of a total debt amount for a plurality of consumers over a period of time; (c) selecting a consumer leverage time series that compares the total income amount to the total debt amount over a period of time; (d) modeling the consumer leverage time series based at least partially on the first and second data; (e) determining, using a processor, the value of the cycle component for a particular time; and (f) outputting an indication of the value of the cycle component for the particular time.