Numerix, the leading provider of cross-asset Analytics for derivatives valuations and Risk Management today announced the results of its latest quantitative research “Algorithmic Exposure and CVA for Exotic Derivatives” contributed to by Alexander Antonov, SVP of Quantitative Research, Serguei Issakov, SVP Quantitative Research & Development and Serguei Mechkov, SVP of Quantitative Research.
“This paper introduces a theoretical framework that can be used to reconcile various approaches to computing risk with the same level of speed and accuracy as pricing, helping to create a common language for the front and middle offices”
The paper establishes a new algorithmic method for calculating Counterparty exposure for exotic portfolios and automates its application to computing Monte Carlo simulated measures for Market Risk and Counterparty Risk, including Monte Carlo VaR (Value at Risk), Expected Shortfall, PFE (Potential Future Exposure) and CVA (Credit Value Adjustment). Recognized as a more advanced measure of Counterparty Risk, and required by Basel III, CVA is an adjustment to the price of any financial instrument due to the possible default of a Counterparty.
Fundamental to this approach is the concept of exposure-centric analytics, which generalizes the existing price-centric analytics, as a rigorous framework for computing Market Risk and Counterparty Risk. As such, this method also naturally lends itself to computing Economic Scenario Generators by applying economic variables to the scenario generation framework.
“I’m proud of the groundbreaking research our dedicated R&D team has brought to market, helping to advance model transparency and increase understanding of today’s complex derivatives market,” said Steven R. O’Hanlon, President and Chief Operating Officer at Numerix. “Under Basel III CVA changes the most fundamental assumptions in OTC derivatives pricing requiring a portfolio and counterparty level view of trades. It can be costly and challenging so we’re honored to present this timely, impactful work.”
