Margin requirement determination and modeling for cleared credit

Patent metadata

Field	Value
Publication number	US-10430880-B2
Application number	US-201514706673-A
Country	US
Kind code	B2
Filing date	May 7, 2015
Priority date	May 16, 2014
Publication date	Oct 1, 2019
Grant date	Oct 1, 2019

Abstract

Systems and methods are provided for calculating margin requirements and stress testing exposures of cleared credit portfolios. These margin requirements are calculated using the following components: spread risk, idiosyncratic risk, interest rate, and liquidity risk. The calculation of these risk components is accomplished with a detailed statistical analysis of the risk factors underlying instruments, such as a credit default swap instrument.

First claim

We claim:

1. A credit default swap (CDS) risk modeling computing system comprising:
a data repository storing a risk model for cleared credit (RMCC), the RMCC being reactive to current market conditions and persistent to extreme events and including both a margin model and a stress model, the stress model being an extension of the margin model;
at least one processor; and
one or more non-transitory memory devices communicatively coupled to the at least one processor, the non-transitory memory devices storing instructions that, when executed by the at least one processor, cause the CDS risk modeling computing system to:
retrieve, the RMCC from the data repository;
process, the RMCC based on a statistical analysis of risk factors underlying components of a portfolio;
receive, from a user interface screen via a network, an input identifying whether a stress evaluation is to be performed using the stress model or a margin calculation is to be performed using the margin model;
calculate, using a spread risk factor calculator, a spread risk factor based on the input and an identification of whether the stress evaluation is being performed or the margin calculation is being performed, the spread risk factor corresponding to a value at risk (VaR) associated with a plurality of correlation scenario sets, wherein the correlation scenario sets correspond to characteristics of at least one of a single name credit default swap or an index credit default swap of the portfolio;
calculate, using an idiosyncratic risk factor calculator, an idiosyncratic risk factor corresponding to a jump-to-default (JTD) charge and a jump-to-health (JTH) charge associated with the portfolio;
calculate, using an interest rate risk factor calculator, an interest rate risk factor corresponding to losses associated with the portfolio due to a change in interest rates, wherein the interest rate risk factor corresponds to at least an upshot loss and a down shock loss;
calculate, using a liquidity risk factor calculator, a liquidity risk factor corresponding to a liquidity charge associated with the portfolio;
when the input indicates the margin calculation is being performed, calculate, by a margin calculator, a margin requirement for the portfolio based, at least in part on the spread risk factor, the idiosyncratic risk factor, the interest rate risk factor, and the liquidity risk factor; or
when the input indicates the stress evaluation is being performed, calculate a stress requirement associated with the portfolio based, at least in part on the spread risk factor, the idiosyncratic risk factor, the interest rate risk factor, and the liquidity risk factor; and
present information corresponding to the calculated stress requirement or the calculated margin requirement.

2. The CDS risk modeling computing system of claim 1 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the spread risk factor calculator to:
model, using a Monte Carlo-based scenario generator, a plurality of risk factors using a symmetric t-copula with four degrees of freedom, wherein an empirical copula associated with risk factor pairs is used to justify a choice of a multivariate copula distribution.

3. The CDS risk modeling computing system of claim 2 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the scenario generator to
receive, at an input to the scenario generator, one or more correlation scenarios comprising a historical correlation matrix, a systemic correlation matrix, and a basis correlation matrix; and
estimate one or more of a base value-at-risk (VaR), a basis VaR, and a systematic VaR based on the one or more correlation scenarios.

4. The CDS risk modeling computing system of claim 3 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the scenario generator to
calculate a margin spread risk factor as a sum of the base VaR and a fraction of a maximum of either the basis VaR and the systematic VaR.

5. The CDS risk modeling computing system of claim 3 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the scenario generator to
calculate a stress spread risk factor as a sum of the base VaR and a fraction of a maximum of either the basis VaR and the systematic VaR, wherein a first quantile of profit and loss (P&L) distributions associated with a stress spread risk factor is greater than a second quantile of P&L distributions associated with a margin spread risk factor.

6. The CDS risk modeling computing system of claim 2 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the scenario generator to:
scale outputs from the symmetric t-copula by a corresponding marginal t-distribution and a forecasted exponential weighted moving average (EWMA) volatility.

7. The CDS risk modeling computing system of claim 6 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the scenario generator to scale an EWMA volatility using a 1-day shock value and a margin period-of-risk shock value.

8. The CDS risk modeling computing system of claim 7 , wherein a multiplier for a EWMA forecast is calibrated to a result of a cross sectional analysis of post or pre Lehman EWMA forecasts across different risk factors.

9. The CDS risk modeling computing system of claim 1 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the idiosyncratic risk factor calculator to:
calculate an overall portfolio VaR associated with the portfolio;
calculate a JTD value-at-risk (VaR) associated with each single name position associated with the portfolio, wherein each JTD VaR comprises a default charge associated with a particular single name position and a remaining portfolio VaR corresponding to a remaining portion of the portfolio after removing the particular single name position;
calculate a maximum JTD VaR of the JTD VaR associated with each single name position; and
calculate the JTD charge as a difference between the maximum JTD VaR and the overall portfolio VaR.

10. The CDS risk modeling computing system of claim 9 , wherein the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the idiosyncratic risk factor calculator to:
calculate the remaining portfolio VaR associated with the portfolio after removing the particular single name position, wherein each index position in the remaining portion of the portfolio is adjusted to account for the removal of the particular single name position; and
calculate the default charge associated with the particular single name position as a difference between a current price of the particular single name position and a minimum recovery rate observed through a history associated with the particular single name position.

11. The CDS risk modeling computing system of claim 9 , wherein, the one or more non-transitory memory devices further store instructions that, when executed by the at least one processor, cause the idiosyncratic risk factor calculator to:
calculate a margin JTD charge associated with the portfolio based on a historical correlation scenario set, wherein the margin JTD charge is used in calculating a margin requirement associated with the

Assignees

• Chicago Mercantile Exchange Inc

Inventors

• Baysal Evren
• Ding Kailin
• Li Nick
• Lu Lu
• Wang Chao
• Xythalis Panos
• Yang Alice
• Zhai Jun

Classifications

• G06Q40/04 Primary

  Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange · CPC title

• G06Q40/06

  Asset management; Financial planning or analysis · CPC title