CCR KVA Relief Through CVA: A Regression-Based Monte Carlo Approach

Wilmott Magazine, January 2019, 42-61

33 Pages Posted: 4 Mar 2018 Last revised: 8 Feb 2019

Date Written: February 6, 2019


We present and examine, by example of a USD interest rate swap and a EUR/USD cross-currency basis swap, a regression-based Monte Carlo approach to counterparty credit default risk (CCR) capital and CCR capital valuation adjustment (KVA) calculations [assuming the standardized approach to counterparty credit risk for exposure-at-default (SA-CCR EAD) and the internal ratings-based (IRB) approach for CCR risk weights]. This approach allows to incorporate the capital lowering effect of credit valuation adjustment (CVA) in an efficient manner, without having to resort to lengthy nested Monte Carlo simulations. We find that the regression-based Monte Carlo approach works well in most situations. In other situations, the accuracy of the approach is sensitively controlled by the choice of explanatory variables. We discuss in detail the conditions and underlying dynamics under which this happens. In computing and presenting a selection of numerical examples, we also explore the impact of dynamic CCR risk weights on CCR KVA, and compare regression-based CCR KVA results with CCR KVA results from nested Monte Carlo, alternative frequently used CCR KVA simplifications, and standardized CVA KVA.

Keywords: regression-based Monte Carlo, CCR capital, CCR KVA, SA-CCR EAD, incurred/ forward CVA, static and dynamic CCR risk weights, Basel III, OTC derivatives

Suggested Citation

Puetter, Christoph M and Renzitti, Stefano and Cowan, Allan, CCR KVA Relief Through CVA: A Regression-Based Monte Carlo Approach (February 6, 2019). Wilmott Magazine, January 2019, 42-61, Available at SSRN: or

Christoph M Puetter (Contact Author)

S&P Global

1066 W Hastings St
Vancouver, British Columbia V6E 3X1

Stefano Renzitti

S&P Global ( email )

1066 West Hastings Street
Vancouver, British Columbia V6E 3X1

Allan Cowan

IHS Markit


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