Numerix has published the results of its latest quantitative research, ‘Algorithmic Exposure and Credit Value Adjustment (CVA) for Exotic Derivatives”, written by Alexander Antonov, Serguei Issakov and Serguei Mechkov of the analytic institution’s quantitative research team.
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 value-at-risk (VaR), expected shortfall, potential future exposure (PFE) and credit value adjustment (CVA).
“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,” said Issakov, senior vice president (SVP) of quantitative research and development.
“While there is a consensus on how to compute price, there are various approaches to achieve risk computations, which don’t always agree with each other. We found that by calculating exposure in parallel with pricing a unified, more efficient approach can be taken to computing complex risk measures.”
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 (ESGs) by applying economic variables to the scenario generation framework.
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