SYSTEM AND METHOD FOR MULTI-FACTOR MODELING, ANALYSIS AND MARGINING OF CREDIT DEFAULT SWAPS FOR RISK OFFSET

• US 20130073479A1
• Filed: 01/30/2012
• Published: 03/21/2013
• Est. Priority Date: 01/07/2005
• Status: Active Grant

• Current Assignee: Chicago Mercantile Exchange, Inc. (CME Group Incorporated)
• Original Assignee: Chicago Mercantile Exchange, Inc. (CME Group Incorporated)
• Inventors: Hadi, Muhammed, Patel, Ketan B., Koblas, Michal, Dedhia, Ankeet, Wang, Mu
• Granted Patent: US 8,738,490 B2
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 99/00 Subject matter not provided for in other groups of this subclass

Abstract

A method for determining a margin requirement associated with a plurality of financial instruments within a portfolio is disclosed. The method includes receiving a plurality of data associated with the plurality of financial instruments within the portfolio, calculating a maximum risk margin for each of the plurality of risk factors such that the maximum risk margin for each of the plurality of risk factors is determined based on the plurality of data, and calculating a total multi-factor risk margin based on maximum risk margin for each of the plurality of risk factors.

Claims

1. A method comprising:

receiving a plurality of data associated with a plurality of financial instruments within a portfolio;

calculating, using a processor, a maximum risk margin for each of a plurality of risk factors, wherein the maximum risk margin for each of the plurality of risk factors is determined based on the plurality of data; and

calculating, using the processor, a total multi-factor risk margin based on the maximum risk margin for each of the plurality of risk factors.

2. The method of claim 1, wherein the plurality of risk factors include a systematic risk factor, the method comprising:

identifying time series spread data of at least one index from the plurality of data;

calculating a plurality of absolute periodical changes from the time series spread data; and

determining the systematic risk shock factor according to a statistical analysis of the plurality of absolute periodical changes.

3. The method of claim 1, wherein the plurality of risk factors include a curve risk factor, the method comprising:

selecting a curve factor based on a type of each of the plurality of financial instruments within the portfolio;

determine a plurality of curve charges based on the curve factor and a notional amount for each of the plurality of financial instruments within the portfolio; and

summing the plurality of curve charge to determine the curve risk factor.

4. The method of claim 1, wherein the plurality of risk factors include a convergence and divergence risk factor, the method comprising:

classifying the plurality of financial instruments within the portfolio according to tenor;

calculating a periodic change in spreads for each tenor;

identifying a largest periodic change in spreads; and

calculating the convergence and divergence risk factor based on the largest periodic change in spreads.

5. The method of claim 4, wherein identifying the largest change in spreads comprises:

selecting a sample regression line having a predetermined slope;

plotting a plurality of pairs of spread changes;

calculating a distance from each of the plurality of pairs of spread changes; and

selecting the distance spaced farthest from the sample regression line.

6. The method of claim 1, wherein the plurality of risk factors include a idiosyncratic risk factor, the method comprising:

selecting a maximum loss of a jump to health value and a jump to default value for each of the plurality of financial instruments within the portfolio; and

summing the maximum loss for each of the plurality of financial instruments within the portfolio to determine the idiosyncratic risk factor.

7. The method of claim 1, wherein the plurality of risk factors include a liquidity risk factor, the method comprising:

selecting an anchor financial instrument from the plurality of financial instruments;

generating a liquidity profile from comparisons of a ratio of the bid-ask spread for each of the plurality of financial instruments to the anchor financial instrument; and

calculating the liquidity risk factor based on the liquidity profile, a duration adjustment, and a present value factor.

8. The method of claim 1, further comprising:

determining a shock value for each of the plurality of risk factors within a multi-factor risk model, wherein the maximum risk is a function of the shock value associated with each of the plurality of risk factors; and

sending data indicative of the total multi-factor risk margin to a device.

9. A method comprising:

receiving, using a processor, a plurality of data associated with a plurality of credit default swaps within a portfolio;

calculating, using the processor, a plurality of maximum risk margins based on at least a portion of the received plurality of data;

calculating, using the processor, a total multi-factor risk margin based on the plurality of maximum risk margins; and

sending data indicative of the total multi-factor risk margin to a device.

10. The method of claim 9 further comprising:

calculating a maximum systematic risk margin based on a first portion of the received plurality of data;

calculating a maximum curve risk margin based on at least a second portion of the received plurality of data; and

calculating a maximum convergence and divergence risk margin based on at least a third portion of the received plurality of data.

11. The method of claim 10 further comprising:

calculating a maximum sector risk margin based on at least a fourth portion of the received plurality of data; and

calculating a maximum idiosyncratic risk margin based on at least a fifth portion of the received plurality of data.

12. The method of claim 11 further comprising:

calculating a maximum liquidity risk margin based on at least a sixth portion of the received plurality of data; and

calculating a maximum basis risk margin based on at least a seventh portion of the received plurality of data.

13. An apparatus comprising:

a database configured to store a plurality of data associated with a plurality of financial instruments within a portfolio;

a margin processor configured to calculate a maximum risk margin for each of a plurality of risk factors, wherein the maximum risk margin for each of the plurality of risk factors is determined based on the plurality of data, and configured to calculate a total multi-factor risk margin based on the maximum risk margin for each of the plurality of risk factors.

14. The apparatus of claim 14, further comprising:

a systematic risk processor configured to identify time series spread data of at least one index from the plurality of data, calculate a plurality of absolute periodical changes from the time series spread data, and determine a systematic risk shock according to a statistical analysis of the plurality of absolute periodical changes, wherein the plurality of risk factors includes the systematic risk shock.

15. The apparatus of claim 14, further comprising:

a curve risk processor configured to select a curve factor based on a type of each of the plurality of financial instruments within the portfolio, determine a plurality of curve charges based on the curve factor and a notional amount for each of the plurality of financial instruments within the portfolio, and sum the plurality of curve charge to determine a curve risk factor, wherein the plurality of risk factors includes the curve risk factor.

16. The apparatus of claim 14, further comprising:

a convergence and divergence risk processor configured to classify the plurality of financial instruments within the portfolio according to tenor, calculate a periodic change in spreads for each tenor, identify a largest periodic change in spreads, and calculate a convergence and divergence risk factor based on the largest periodic change in spreads, wherein the plurality of risk factors includes the convergence and divergence risk factor.

17. The apparatus of claim 16, wherein the convergence and divergence risk processor is configured to select a sample regression line having a predetermined slope, calculate a distance from each of a plurality of pairs of spread changes and select the distance spaced farthest from the sample regression line to define the convergence and divergence risk factor.

18. The apparatus of claim 14, further comprising:

an idiosyncratic risk processor configured to select a maximum loss of a jump to health value and a jump to default value for each of the plurality of financial instruments within the portfolio and sum the maximum loss for each of the plurality of financial instruments within the portfolio to determine an idiosyncratic risk factor, wherein the plurality of risk factors includes the idiosyncratic risk factor.

19. The apparatus of claim 14, further comprising:

a liquidity processor configured to select an anchor financial instrument from the plurality of financial instruments, generate a liquidity profile from comparisons of a ratio of the bid-ask spread for each of the plurality of financial instruments to the anchor financial instrument, and calculate a liquidity risk factor based on the liquidity profile, a duration adjustment, and a present value factor, wherein the plurality of risk factors includes the liquidity risk factor.

20. The apparatus of claim 14, wherein the plurality of financial instruments includes a plurality of credit default swaps.