the counterparty, the CVA increases as it is marked to market. On the other hand, a profit is reported if the CVA decreases, due either to the bank's position becoming less in the money, an improvement in the counterparty's credit rating, or just the passage of time without any credit event. However, no further credit-related charges or costs are incurred by the business. In the limit, the CVA disappears as the maturity of the derivative contract is reached, and payment – if any is due – is made to the bank.
Products that are new or too complex to be properly simulated within the main CCR engine are dealt with “offline.” This usually means assigning them “risk factors” or more generally “add-ons” that are conservative and do not allow for netting; for this reason, such offline trades may account for up to 50 percent of the total exposure, although only 5 to 10 percent of trades made. The problem is that the counterparty credit exposure (CCE) is not sensitive to actual risk any longer: The sum of these add-ons may lead to the same measure of CCE for a set of offsetting trades as it does for a set of trades that have no offsets. Hence, these add-ons are really suited only for CCE with counterparties having single trades. Moreover, the large exposures they generate are not taken seriously by management, and these products do not undergo the complementary/downstream risk management processes such as stress testing, which results in risk measures that do not provide a comprehensive view of the risks that banks face. Worse still, management may increase limits for these products, aware that their CCR is overstated, thus defeating the purpose of these add-ons.
A relatively new but expanding practice is to model debt valuation adjustment (DVA) in the CCR framework, reflecting an institution's own option to default. Counterparties implicitly charge for an option to default, as when an institution holding a derivative position that is out of the money is in effect borrowing from the counterparty and implicitly pays for its outstanding liability through its credit spread. One way for a bank to fund its CVA would be to generate income from the sale of credit default swaps on itself, which cannot be done, hence the remaining portion of credit risk as reflected by the CVA. However, note that such “gut ” appeal DVA stems from the realization that if a bank enters a par swap agreement with a counterparty that has the same credit spread, then theoretically, credit risk considerations should not enter the pricing decision (i.e., the CVA and DVA should cancel for both parties in the transaction).
Analogous to the CVA, scenarios for underlying market factors are generated and averaged over the resultant negative portfolio marked-to-market values (liabilities), taking into account legal netting and collateral agreements. The resulting expected negative exposure, floored at zero if a bank gets in the money in any given scenario, is what risk managers expect to owe its counterparties on its derivative portfolio at the time of its default. It is priced as the contingent leg of a credit default swap using the bank's bank spreads, assuming that all deals are netted where possible, reflecting the fact that within the bank's jurisdiction it is likely that its counterparties would legally seek to net all positions upon its default.
For collateral considerations, often two types of default are considered. First, consider the case in which a bank defaults idiosyncratically, and a “springing” unilateral collateral agreement is assumed. This reflects the likely behavior of counterparties, who upon a worsening of a bank's credit worthiness will either demand to enter into unilateral collateral agreements where there are none or renegotiate existing collateral agreements to terms favorable to them. Second, there is the case of a systemic default, where a bank's default is part of a broad economic downturn. In this case it is much less clear that counterparties will be able to impose or change collateral agreements in their favor, and thus springing collateral is not considered. The final expected negative exposure value is a weighted average of the two cases, such that the relative weight is the relative likelihood of an idiosyncratic as opposed to a systematic default. These weights could be determined by the relative intensities of default implied by a bank's par spread curve and its risk premium spread curve backed using a capital asset pricing model methodology.
Review of the Literature
Supervisory rules and guidance on CCR can be found in the Basel Committee on Banking Supervision (BCBS) frameworks of Basel I (BCBS, 1988); Basel II (BCBS, 2006); Basel III (BCBS, 2011); and BCSB (2012). The U.S. Office of the Comptroller of the Currency (OCC) and the Board of Governors of the Federal Reserve System (BOG-FRS) issued supervisory guidelines (OCC & BOG-FRS 2011). Kang and Kim (2005) provide simple closed-form pricing models for floating-rate notes and vulnerable options under the CCR framework, deriving closed-form pricing models for them and illustrating the impact of the counterparty default intensity on the prices of floating-rate notes and vulnerable options.
Brigo and Chourdakis (2009) consider CCR for credit default swaps when default of the counterparty is correlated with default of the CDS reference credit. They incorporate credit spread volatility, adopt stochastic intensity models for the default events, and connect defaults through a copula function. The authors find that both default correlation and credit spread volatility have a relevant impact on the positive CCR valuation adjustment to be subtracted from the counterparty risk-free price. Jorion and Zhang (2009) observe that standard credit risk models cannot explain the observed clustering of default, sometimes described as “credit contagion,” and provide the first empirical analysis of credit contagion via direct counterparty effects. They find that bankruptcy announcements cause negative abnormal equity returns and increases in CDS spreads for creditors, and that creditors with large exposures are more likely to suffer from financial distress later, suggesting that counterparty risk is a potential additional channel of credit contagion. Arora, Gandhi, and Longstaff (2012) use proprietary data from 14 CDS dealers and find that counterparty risk is priced in the CDS market and the magnitude of the effect is small. Brigo, Capponi, Pallavicini, and Papatheodorou (2013) value bilateral CCR through stochastic dynamical models when collateral is included with possible rehypothecation. The authors show for credit default swaps that a perfect collateralization cannot be achieved under default correlation.
Brigo, Buescu, and Morini (2012) compare two different bilateral counterparty valuation adjustment formulas (an approximation based on subtracting the two unilateral credit valuation adjustment formulas as seen from the two different parties in the transaction) and a fully specified bilateral risk formula where the first-to-default time is taken into account. Finally, Acharya and Bisin (2014) study financial markets where agents share risks but have incentives to default and their financial positions might not be transparent, that is, not mutually observable. The authors show that a lack of position transparency results in a counterparty risk externality, which manifests itself in the form of excess “leverage” in that parties take on short positions that lead to levels of default risk that are higher than Pareto-efficient ones.
Supervisory Requirements for CCR
CCR is defined as the risk that the counterparty to a transaction could default or deteriorate in creditworthiness before the final settlement of a transaction's cash flows. Unlike a loan, where only a bank faces the risk of loss, CCR creates a bilateral risk of loss because the market value of a transaction can be positive or negative to either counterparty. The future market value of the exposure and the counterparty's credit quality are uncertain and may vary over time as underlying market factors change. The regulatory focus is on institutions with large derivatives portfolios setting their risk management practices as well as on supervisors as they assess and examine CCR management.
CCR is multidimensional, affected by both the exposure to and credit quality of the counterparty, as well as their interactions, all of which are sensitive to market-induced changes. Constructing an effective CCR management framework requires a combination of risk management techniques from the credit, market, and operational risk disciplines. CCR management techniques have evolved rapidly and improved over the last decade even as derivative instruments under management have increased in complexity. While institutions substantially improved their risk management practices, in some cases implementation of sound practices has been uneven across business lines and counterparty types. The financial crisis of 2007–2009 revealed weaknesses in CCR management of timely and accurate
