Abstract
Considering counterparty credit risk (CCR) for derivatives using valuation adjustments (CVA) is a fundamental and challenging task for entities involved in derivative trading activities. Particularly calculating the expected exposure is time consuming and complex. This paper suggests a fast and simple semi-analytical approach for exposure calculation, which is a modified version of the new regulatory standardized approach (SA-CCR). Hence, it conforms with supervisory rules and IFRS 13. We show that our approach is applicable to multiple asset classes and derivative products, and to single transactions as well as netting sets.
Highlights
The financial crisis and its aftermath have revealed the importance of counterparty credit risk (CCR) in over-the-counter (OTC) derivative transactions
As we maintain the key building blocks and methodological assumptions of the supervisory SA-CCR, we offer a flexible and consistent approach to calibration based on market-implied volatilities, yet simple enough to be adopted by smaller institutions with limited personal resources
We are able to recognize these characteristics in the modified SA-CCR via a ca√sh flow based calculation of replacement costs as well as the scaling of the add-on by t
Summary
The financial crisis and its aftermath have revealed the importance of counterparty credit risk (CCR) in over-the-counter (OTC) derivative transactions. International financial reporting standards (IFRS 13) require all entities involved in derivative transactions to consider CCR in the accounting fair value.. Most existing approaches are either too simplistic to be robust, only applicable on transaction level or suitable for a small range of products Most of these methods are not applicable to multidimensional netting sets. The second step was based on a comparison of SA-CCR exposure outcomes with results from simplified IMM models for a set of hypothetical portfolios. This comparison was carried out for small portfolios involving hypothetical trades for each asset class. The model outcomes were averaged and compared with CEM and SA-CCR exposures to derive final adjustments to the regulatory parameters
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