Chicago Mercantile Exchange Inc.

Jennifer Yingying Weng

Guo Chen

Shuo Liu

Nikhil Joshi

Zijiang Yang

Siwen Yang

Sebastiano Rossi

Xiaowen Xu

Xianqing Zou

Ziyi Wang

Yingwen Liu

Chenda Huang

Panagiotis Xythalis

Jie Zhu

Abhinaw Prakash

Nataliya Frost

Lingrui Xiang

Hariharan Kesavarao

A method and system are disclosed for more efficiently constructing a volatility surface. The methodology results in measurable reduction in the quantity of storage memory space needed on a computer executing the novel methodology, reduces the measurable, on-demand computational load on the processor(s) of a computer executing the novel methodology, and permits as-of-day calculations of the volatility surface that were previously impossible to obtain in near real-time.

Computer methodology providing as-of-day volatility surface construction for pricing

A physical container (e.g., a battery) may be filled up (charged) or emptied (discharged) with energy commensurate with requirements to post a particular amount of collateral. The disclosure provides computing systems and methods for processing data using a novel combination of wavelet techniques and rolling techniques to more efficiently detect seasonality in particular products (e.g., energy products) to more accurately model and determine collateral/margin requirements. A clearinghouse computing device may be configured to generate a margin requirement for a portfolio of products and may include a processor to process instructions that cause the clearinghouse computing device to perform wavelet decomposition and rolling methods on a historical database of records.

Futures margin modeling system having seasonality detection

A system may be configured to generate an estimate of value at risk and may include a processor to process instructions that cause the system to generate a rolling time series of value data having a plurality of dimensions, perform rotation transform of the time series, perform variance scaling and correlation scaling on transformed time series, reverse transform the results of the scaling, and estimate of a value-at-risk for the value data.

Futures margin modeling system

A clearinghouse computing device may be configured to generate a margin requirement for a portfolio of financial products and may include a processor to process instructions that cause the clearinghouse computing device to retrieve a plurality of pricing records from a historical pricing database, process the plurality of pricing records to generate rolling time series pricing records for at least one financial product having a plurality of dimensions, reduce the number of dimensions from a starting dimension to a reduced dimension, perform variance scaling and correlation scaling on the reduced dimension rolling time series pricing records, and generate a margin requirement based on a value-at-risk calculation.

Electric battery recharging unit controlled by a seasonality detection unit of a futures margin modeling system

A method and system are disclosed for more efficiently constructing a volatility surface. The methodology results in measurable reduction in the quantity of storage memory space needed on a computer executing the novel methodology, reduces the measurable, on-demand computational load on the processor(s) of a computer executing the novel methodology, and also permits as-of-day calculations of the volatility surface that were previously impossible to obtain in near real-time.

Datasets may be characterized by patterns. The patterns may be caused or otherwise influenced by external factors, such as temporal, meteorological, and/or system factors. The external factors, as well as the patterns which result in the data values of the dataset because of the external factors, may provide for techniques used to account for missing data elements, outlier data elements and/or otherwise cleanse the dataset. New elements may be generated to provide for the missing data elements, and derivative datasets may be generated based on one or more cleansed datasets.

Dataset cleansing

Growing community of inventors

Brooklyn, NY, United States of America

Jennifer Yingying Weng