Multi-asset portfolio simulation (MAPS)

Patent metadata

Field	Value
Publication number	US-10817947-B2
Application number	US-201816046190-A
Country	US
Kind code	B2
Filing date	Jul 26, 2018
Priority date	Jun 17, 2013
Publication date	Oct 27, 2020
Grant date	Oct 27, 2020

Abstract

An exemplary system according to the present disclosure comprises a computing device that in operation, causes the system to receive financial product or financial portfolio data, map the financial product to a risk factor, execute a risk factor simulation process involving the risk factor, generate product profit and loss values for the financial product or portfolio profit and loss values for the financial portfolio based on the risk factor simulation process, and determine an initial margin for the financial product. The risk factor simulation process can be a filtered historical simulation process.

First claim

The invention claimed is:

1. A computer implemented method of collateralizing counterparty credit risk, the method comprising:
receiving as input, by at least one computing device, data defining at least one financial product, said computing device comprising memory and at least one processor executing computer-readable instructions;
mapping, by the at least one computing device, the at least one financial product to at least one risk factor;
executing, by the at least one computing device, a risk factor simulation process involving the at least one risk factor, said risk factor simulation process comprising:
retrieving, by the at least one computing device from a data source, historical pricing data for the at least one risk factor; and
executing a filtered historical simulation process by applying a scaling factor to said historical pricing data to resemble current market volatility, said scaling factor reflecting the statistical properties and co-dependencies of said historical pricing data;

generating, by the at least one computing device, product profit and loss values for the at least one financial product based on output from the risk factor simulation process;
determining, by the at least one computing device, an initial margin for the at least one financial product based on the product profit and loss values;
forecasting future return volatility of the at least one financial product based on the scaled historical pricing data that resembles the current market volatility;
assigning a dollar value of the at least one financial product based on said future return volatility; and
collecting an initial margin value reflective of said dollar value, thereby collateralizing counterparty credit risk associated with said at least one financial product.

2. The method of claim 1 , wherein said mapping comprises identifying at least one risk factor that affects a profitability of the at least one financial product.

3. The method of claim 1 , wherein the risk factor simulation process further comprises:
determining, by the at least one computing device, statistical properties of the historical pricing data;
identifying, by the at least one computing device, any co-dependencies between prices that exist within said historical pricing data; and
generating, as said output, normalized historical pricing data based on said statistical properties and said co-dependencies.

4. The method of claim 3 , wherein generating the product profit and loss values comprises
calculating, via a pricing model embodied in the at least one computing device, one or more forecasted prices for the at least one financial product based on the normalized historical pricing data input into said pricing model; and
comparing each of said forecasted prices to a current settlement price of the at least one financial product to determine a product profit or loss value associated with each of said forecasted prices.

5. The method of claim 4 , wherein determining the initial margin comprises
sorting the product profit and loss values, most profitable to least profitable or vice versa; and
selecting the product profit or loss value among the sorted values according to a predetermined confidence level,
wherein the selected product profit or loss value represents said initial margin.

6. The method of claim 5 , wherein the historical pricing data comprises pricing data of the at least one risk factor over a period of at least one-thousand (1,000) days, the method further comprising
calculating, via said pricing model, one-thousand forecasted prices, each based on the normalized pricing data pertaining to a respective one of the one-thousand days;
determining, by the at least one computing device, a product profit or loss value associated with each of the one-thousand forecasted prices by comparing each of the one-thousand forecasted prices to a current settlement price of the at least one financial product;
sorting, by the at least one computing device, the product profit and loss values associated with each of the one-thousand forecasted prices from most profitable to least profitable or vice versa; and
identifying, by the at least one computing device, a tenth least profitable product profit or loss value,
wherein said tenth least profitable product profit or loss value represents the initial margin, and
wherein said tenth least profitable product profit or loss value represents a ninety-nine percent confidence level.

7. A computer implemented method of collateralizing counterparty credit risk, the method comprising:
receiving as input, by at least one computing device, data defining at least one financial portfolio, the at least one financial portfolio comprising at least one financial product, said computing device comprising memory and at least one processor executing computer-readable instructions;
mapping, by the at least one computing device, the at least one financial product to at least one risk factor;
executing, by the at least one computing device, a risk factor simulation process involving the at least one risk factor, said risk factor simulation process comprising:
the at least one computing device from a data source, historical pricing data for the at least one risk factor; and
executing a filtered historical simulation process by applying a scaling factor to said historical pricing data to resemble current market volatility, said scaling factor reflecting the statistical properties and co-dependencies of said historical pricing data;

generating, by the at least one computing device, product profit and loss values for the at least one financial product based on output from the risk factor simulation process;
generating, by the at least one computing device, portfolio profit and loss values for the at least one financial portfolio based on the product profit and loss values;
determining, by the at least one computing device, an initial margin for the at least one financial portfolio based on the portfolio profit and loss values;
forecasting, by the at least one computing device, future return volatility of the at least one financial portfolio based on the scaled historical pricing data that resembles the current market volatility;
assigning a dollar value of the at least one financial portfolio based on said future return volatility; and
collecting an initial margin value reflective of said dollar value, thereby collateralizing counterparty credit risk associated with said at least one financial portfolio.

8. The method of claim 7 , wherein said mapping comprises identifying at least one risk factor that affects a probability of the at least one financial product.

9. The method of claim 7 , wherein the risk factor simulation process further comprises:
determining, by the at least one computing device, statistical properties of the historical pricing data;
identifying, by the at least one computing device, any co-dependencies between prices that exist within said historical pricing data; and
generating, as said output, normalized historical pricing data based on said statistical properties and said co-dependencies.

10. The method of claim 9 , wherein generating product profit and loss values comprises
calculating, via a pricing model embodied in the at least one computing device, one or more forecasted prices for the at least one financial product based on the normalized historical pricing data input into said pricing model; and
comparing each of said forecasted prices to a current settlement price of the at least one financial product to determine a product profit or loss value associated with each of said forecasted prices.

11. The method of claim 10 , wherein the generat

Assignees

• Intercontinental Exchange Holdings Inc

Inventors

• Weber Michael G
• Ivanov Stanislav I
• Vice Charles A
• Gibson Michael
• Yang Yunke
• Atre Vikram
• Shapiro Joshua I
• Morrison Judson H
• Shively Bradley D
• Routray Sidhartha
• Hopper Michael A
• Jefson Thomas W
• Cummings R J
• Ensign Jacob S
• O'Shields Jeremy K
• Pounds Stephen R
• Shepherd Eric D J
• Iyigunler Ismail

Classifications

• G06Q40/06 Primary

  Asset management; Financial planning or analysis · CPC title