After the 2007 crisis, CCR was identified as one of the major cause of the turmoil in the financial market, and mostly materialised through downgrade and loss in value, more than actual defaults.
Current hot topics include: Are CCPs the optimal answer to manage counterparty risk or are they creating more issues than they solve? Banks are insisting on the huge potential systemic risk related to the probability of a CCP default, which would be highly contagious to the financial markets. In some ways, regulators may be creating an even higher “too big to fail” problem. Moreover, the modeling part of that risk becomes extremely complex because exposures cannot be identified any more for the other institutions dealing with the CCP. Other typical issues are related to moral hazard, netting across asset classes, operational risks, or to the maturity level of the models in place.
When should institutions apply risk neutral probabilities, and when should they use real world probabilities for measuring Counterparty Credit Risk?
There is a recurring question on the nature of Credit Value Adjustment (CVA): should the default probability measure applied to CCR be risk neutral (e.g. extracting the term structure of the default probability from market CDS prices) or should it be real world (e.g. based on internal or external ratings)? The regulation currently leaves the choice open to the institution. In that regard the right answer depends on the strategy of the financial institution itself. If the institution is capable of actively managing its CCR, which means both the means to properly manage and measure risk in real time, market implied probabilities should be used. In advanced institutions with mature CVA desks, CVA would be in most cases computed, market based and complemented by some real world risk measures, while for less advanced institutions, the use of real world CVA can be considered.
How can an institution optimize its use of CSA, what should be the nature of SCSA and is it going to fully replace traditional CSA?
One more key discussion is on the Funding Value Adjustment (FVA) and on how it should be measured and possibly optimized in regards to the Credit Support Annexes (CSAs). FVA can be considered as the sum of the expected costs (FCA) and benefits (FBA) due to the funding over the life of a trade. However, to obtain a correct measure of it, it needs to be clarified what collaterals will be posted or received as defined by the CSA Many experts take the position that this issue should be resolved in the long term by the use of Standard CSA (SCSA) following the work currently achieved by the International Swaps and Derivatives Association (ISDA).
Should institutions recognise benefits due to their own credit deterioration, and how can adverse effects be mitigated?
Another recurring topic is the recognition of a Benefit in the form of the debt value adjustment (DVA) in financial institutions P&L. This means that the higher the default probability of the institution, the lower the fair value of its current debt, since it will cost the institution more to borrow money on the market. Therefore, a higher CDS spread can translate itself in direct accounting benefits. This effect is controversial since it gives a sort of “reward” to the institutions from a worsening of its credit quality.
"There are currently discussions, both in the US and in Europe regarding a full implementation of Basel III. One of the key issues is related to the negative spiral effect induced by CVA hedging which could lead to a higher volatility of credit spreads on the market."
What are the main sources of WWR, how can they be measured and managed, specifically for systematically important institutions and in adverse situations?
Potential acceleration effects, identified as Wrong-Way Risk (WWR) can materialise when exposure at risk increases at the same time as credit quality of the counterparty deteriorates. The issue is then to correctly identify and model these effects. The first effect is the specific WWR related to the structure of the transactions at the netting set level. The second effect includes contagion and macroeconomic effects that can be difficult to model, specifically for systematically important counterparties.
How do you best integrate margin periods of risk when modeling counterparty credit risk?
This question is also frequently addressed. It is related to the correct application of the margin period of risk for EAD valuation models handling netting sets (5, 10 or 20 business days). As models developed to assess CCR are already extremely complex, the addition of this dimension of risk can be particularly resource consuming.
Will CVA capital requirements be effectively introduced for all counterparty types as designed by Basel III?
There are currently discussions, both in the US and in Europe regarding a full implementation of Basel III. One of the key issues is related to the negative spiral effect induced by CVA hedging which could lead to a higher volatility of credit spreads on the market. Explained simply, this occurs when the credit spread of a counterparty widens, which increases the CVA charge, which has then to be compensated by additional hedging with CDS contracts that themselves put pressure on the credit spread of the counterparty. Therefore, the European Parliament is poised to defend a CVA exemption for trades with corporate end-users, pension schemes and sovereign entities championed by the Council. This CRD IV negotiation is currently entering its final stage (November 2012). Also, in the US, banking leaders are currently defending a strong pushback of the Basel III regulation.
Managing Counterparty Credit Risk - Part 1: Why Measure Counterparty Credit Risk?
Banks Are Not Ready for Counterparty Risk Elements of Basel lll
Case Study: Helaba Enhances Enterprise-Wide Derivatives Counterparty Risk Management
Optimising Capital Requirements for Counterparty Credit Risk
Challenges in Implementing a Counterparty Risk Management Process