The current interest in the topic of counterparty credit risk (CCR) and its exposure measurement began with the upcoming of the financial crisis, or to be more precise the bankruptcy of Lehman Brothers. Before then, the default of a counterparty of that size was out of the realm of possibility. The default of a counterparty that formerly was assumed as “too big to fail” prompted the need for a reconsideration of credit risk (Moser 2014, p. 429). Among the scope of topics associated with CCR, the determination of the exposure amount is seemingly trivial, but turns out to be highly complex due to the impact of risk mitigants, and the uncertainty involved.
Canabarro and Duffie define counterparty exposure as the larger of zero and the market value of the portfolio of derivative positions with a counterparty that would be lost if the counterparty defaults and there is zero recovery. If the contract value is positive for the bank at the point of the counterparties’ default, the banks net loss equals the contract’s market value. If the contract value is negative, the bank does not gain anything but has a net loss of zero. From a regulatory point of view the Basel Committee on Banking Supervision (BCBS) aims to identify the exposure at default (EAD) which is up stake in the case of a counterparty’s default, which then has to be backed due to capital requirements.
In this main section of the paper an indepth analysis on the characteristics of credit risk exposure and its quantification will be conducted.
At first, the used metrics will be outlined, their characteristics described, and the risk mitigants netting and collateral considered. Last, it will be analyzed for which application the presented measures are suitable and whether they shall be calculated by riskneutral or historical data.
Table of Contents
List of Abbreviations
Table of Figures
1. Introduction
2. Assessment on counterparty credit exposure
2.1. Metrics and characteristics
2.1.1. Metrics of counterparty credit exposure
2.1.2. Driving factors
2.1.3. The impact of netting
2.1.4. The role of collateral
2.1.5. Measurement objectives and their implications for modeling
2.2. Quantification of credit risk exposure
2.2.1. Risk management counterparty exposure: Add-on method
2.2.2. Pricing counterparty exposure: CVA
2.2.3. Monte Carlo simulation
3. Summary
Appendix
References
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