US 11,966,977 B2
Guarantee fund calculation with allocation for self-referencing risk
Evren Baysal, Chicago, IL (US); Panagiotis Xythalis, Scotch Plains, NJ (US); Kailin Ding, Chicago, IL (US); Sixiang Li, Chicago, IL (US); Lu Lu, Pittsburgh, PA (US); and Jun Zhai, Chicago, IL (US)
Assigned to Chicago Mercantile Exchange Inc., Chicago, IL (US)
Filed by Chicago Mercantile Exchange Inc., Chicago, IL (US)
Filed on Mar. 7, 2023, as Appl. No. 18/118,284.
Application 18/118,284 is a continuation of application No. 17/503,884, filed on Oct. 18, 2021, granted, now 11,625,786.
Application 17/503,884 is a continuation of application No. 16/679,787, filed on Nov. 11, 2019, granted, now 11,182,857, issued on Nov. 23, 2021.
Application 16/679,787 is a continuation of application No. 14/839,342, filed on Aug. 28, 2015, granted, now 10,504,186, issued on Dec. 10, 2019.
Prior Publication US 2023/0206336 A1, Jun. 29, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/00 (2023.01); G06Q 40/06 (2012.01); G06Q 40/08 (2012.01)
CPC G06Q 40/06 (2013.01) [G06Q 40/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer implemented method including:
generating a self-referencing risk (SRR) data structure in a memory storage by:
parsing independent operations into a multiple-core processing scheme including operating multiple hardware processing cores in parallel, the multiple hardware processing cores include cores disposed on multiple separate hardware processors;
determining a margin requirement value based on a margin model, the margin model including a scenario model that is extensible to newly determined risk factors;
populating, by a processor coupled with the memory storage and using the multiple-core processing scheme, a residual vector of the SRR data structure by removing, for each of multiple participant units, the margin requirement value from an exposure value to determine a corresponding residual vector entry for the participant unit;
determining, based on the residual vector, at least a predetermined number of top-magnitude residual vector entries;
summing, by the processor, at least the predetermined number of top-magnitude residual vector entries to simulate an event corresponding to the predetermined number of jump-to-defaults occurring to generate a total event value;
populating, by the processor and using the multiple-core processing scheme, a weight vector of the SRR data structure by determining, for each of the multiple participant units, a corresponding ratio value by dividing the corresponding residual vector entry for the participant unit by the total event value; and
populating, by the processor and using the multiple-core processing scheme, a contribution vector of the SRR data structure by multiplying, for each of multiple participant units, the corresponding ratio value for that participant unit to a sum over an entirety of the residual vector, wherein:
the computation for each entry within any one of the vectors is independent of any computation for any other entry in that vector.