CME Group has patented a computer-implemented method for determining guarantee funds for clearing member firms efficiently. The method involves generating a self-referencing risk data structure in memory storage, utilizing multiple-core processing, and simulating events to calculate total event value. The system accounts for exposure to self-referencing risk. GlobalData’s report on CME Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on CME Group, was a key innovation area identified from patents. CME Group's grant share as of April 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.
Efficient determination of guarantee funds for clearing member firms
A recently granted patent (Publication Number: US11966977B2) discloses a computer-implemented method for generating a self-referencing risk (SRR) data structure in memory storage. The method involves parsing independent operations into a multiple-core processing scheme, determining a margin requirement value based on a margin model, and populating various vectors within the SRR data structure. These vectors include a residual vector, a weight vector, and a contribution vector, each calculated independently for multiple participant units. The method simulates events based on the residual vector entries and involves complex computations that are independent of each other within the vectors.
Furthermore, the patent includes claims for non-transitory machine-readable media and a system implementing the method described above. The system comprises a processor and memory configured to execute instructions for generating the SRR data structure. The processor operates multiple hardware processing cores in parallel and determines top-magnitude residual vector entries to simulate events. The margin model used in the method is extensible to newly determined risk factors and covers a risk horizon of at least five days. Additionally, the system includes provisions for time series analysis of risk factors within the margin model, enhancing its adaptability and accuracy in assessing risks over time. Overall, the patented method and system offer a sophisticated approach to risk assessment and management, particularly in scenarios involving multiple participant units and complex financial exposures.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
