non-default before the point in question, because the possibility of an earlier default is captured via a limit at a previous time.
Credit limits are typically used to assess trading activity on a dynamic basis. Any transaction that would breach a credit limit at any point in the future is likely to be refused unless specific approval is given. Limits could be breached for two reasons: either due to new transactions or market movements. The former case is easily dealt with by refusing transactions that would cause a limit breach. The latter is more problematic, and banks sometimes have concepts of hard and soft limits: the latter may be breached through market movements rather than new transactions, whereas a breach of the former would require remedial action (e.g. transactions must be unwound or restructured, or hedges must be sourced). For example, a credit limit of $10m (“soft limit”) might restrict trades that cause an increase in PFE above this value, and may allow the PFE to move up to $15m (“hard limit”) as a result of changes in market conditions. When close to a limit, only risk-reducing transactions would be approved. Due to the directional nature of end-users activity in OTC derivatives, this is a challenge.25
Credit limits allow a consolidated view of exposure with each counterparty and represent a first step in portfolio counterparty risk management. However, they are rather binary in nature, which is problematic. Sometimes a given limit can be fully utilised, preventing transactions that may be more profitable. Banks have sometimes built measures to penalise transactions that are close to (but not breaching) a limit, requiring them to be more profitable, but these are generally quite ad hoc.
Traditional counterparty risk management, as described above, works in a binary fashion. The problem with this is that the risk of a new transaction is the only consideration, whereas the return (profit) should surely be a factor also. By pricing counterparty risk through CVA, the question becomes whether it is profitable once the counterparty risk component has been “priced in”. The calculation of CVA (and DVA) will be discussed in more detail in Chapter 14, but in addition to the components required for PFE quantification mentioned above, the following are also important:
• the default probability and expected LGD of the counterparty; and
• the parties’ own default probability (in the case of bilateral pricing and DVA).
An important aspect of CVA is that it is a counterparty level calculation.26 CVA should be calculated incrementally by considering the increase (or decrease) in exposure, taking into account netting effects due to any existing trades with the counterparty. This means that CVA will be additive across different counterparties and does not distinguish between counterparty portfolios that are highly concentrated. Such concentration could arise from a very large exposure with a single counterparty or exposure across two or more highly correlated counterparties (e.g. in the same region or sector).
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