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Transparent & Independent implementation of

SA-CCR & xVA

About Us

Real world Quantitative Risk Software solutions

Twenty five years of combined experience in the financial and the software industry via two senior cofounders. This is distributed among major financial software providers including Calypso Technologies, banks, hedge funds and consultancies.



Our solutions have matured over the past years via feedback received from professionals working in:

  • Tier I Banks.

  • Big Three Credit Ratings Agencies.

  • Major Buy Side Institutions.

Also, academics from all around the world have utilised our systems and provided valuable feedback.

Our Services

Regulatory Compliance

Is there a SACCR regulatory deadline coming up and you neither have the time nor the budget for a 'traditional' implementation?

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Emergency Management

Did a credit crisis create the need for a quick and reliable counterparty exposure evaluation?

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Model Validation

Do you need a benchmark model to test your CCR exposure or CVA calculations?

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Open source solutions training/adjustment

Do you want to understand how our open source packages work or to enhance them? Please note that our commercial solutions are a few steps ahead, thus, we may offer you what you need at no time.

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SA-CCR

Full implementation of the standardised approach of the Counterparty Credit Risk calculation under CRR2

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xVA

An Implementation of the Valuation Adjustments' universe including CVA, DVA, FVA, MVA and KVA

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SA-CCR R Package

Computes the Exposure-At-Default based on the standardized approach of CRR2 (SA-CCR). The simplified version of SA-CCR has been included, as well as the OEM methodology. Multiple trade types of all the five major asset classes are being supported including the 'Other' Exposure and, given the inheritance- based structure of the application, the addition of further trade types is straightforward. The application returns a list of trees per Counterparty and CSA after automatically separating the trades based on the Counterparty, the CSAs, the hedging sets, the netting sets and the risk factors. The basis and volatility transactions are also identified and treated in specific hedging sets whereby the corresponding penalty factors are applied. All the examples appearing on the regulatory papers (both for the margined and the un-margined workflow) have been implemented including the latest CRR2 developments.. We have developed an implementation of this framework in R and you can browse through its documentation, view the full source code or just download it from R Studio (it appears on the package list as SACCR) .

Some of the features of the application:

  • A tree-based structure is returned as a result which makes drilling into the underlying calculations and the contribution of each trade straightforward.

  • The application automatically separates the trades on the corresponding hedging and netting sets.

  • The algorithm caters for the case of multiple netting agreements per counterparty.

  • The basis and volatility transaction are identified and the relevant penalty factors are applied.

  • Multiple features described in the FAQs and technical standards have been implemented, including the adjustments needed for the negative interest rates cases.

  • All the examples appearing on the regulatory paper (including the margined and the un-margined workflow) have been implemented.

SA-CCR Calculator

Below you can see a sample SA-CCR Calculator which is provided strictly for educational purposes. It supports only a single counterparty & netting set, please contact us for the full version.

xVA R Package

An implementation of the xVA world including CVA, DVA, FBA, FCA, MVA and KVA(under CEM, SA-CCR and IMM). xVA groups as an acronym all the possible credit risk valuation adjustments currently suggested in the market. Starting from CVA which incorporates the default risk of the counterparty in the market price of the trade, the industry proceeded with DVA which is actually the CVA as seen from the counterparty’s point of view and it further continued adding terms, for example FVA which represents the benefit/cost of funding the MtM of a trade due to imperfect collateralization, the MVA which is linked to the initial margin which needs to be posted to the counterparty or the CCP and the KVA which is the effect of the regulatory capital that banks need to hold for this transaction. You can find further info about xVA in in the latest book of Jon Gregory: “the xVA Challenge”. We have developed an implementation of this framework in R and you can browse through its documentation, view the full source code or just download it from R Studio (it appears on the package list as xVA).

Some of the features of the application:

  • Calculates a number of valuation adjustments including CVA, DVA, FBA, FCA, MVA and KVA.

  • A two-way margin agreement has been implemented.

  • For the KVA calculation the following regulatory frameworks are supported: CEM, (simplified) SA-CCR, OEM and IMM..

  • The probability of default is implied through the credit spreads curve.

  • Currently, only IRSwaps are supported for the simulated-based exposure calculation, however, if the input from SA-CCR is utilized then multiple asset classes can be covered - please Contact us for further support.

Trading R Package

Contains performance analysis metrics of track records including entropy-based correlation and dynamic beta based on the Kalman filter. The normalized sample entropy method has been implemented which produces accurate entropy estimation even on smaller datasets while for the dynamic beta calculation the Kalman filter methodology has been utilized. On a separate stream, trades from the five major assets classes and also functionality to use pricing curves, rating tables, CSAs and add-on tables. The implementation follows an object oriented logic whereby each trade inherits from more abstract classes while also the curves/tables are objects. There is a lot of functionality focusing on the counterparty credit risk calculations however the package can be used for trading applications in general. We have developed an implementation of the above in R and you can browse through its documentation, view the full source code or just download it from R Studio (it appears on the package list as Trading).

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Real world Quantitative Risk Software based on solid working experience in the financial industry.

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