LO 18.3: Define default risk, recovery risk, exposure risk and calculate exposure at default.
As mentioned, default risk relates to a borrowers inability to make promised payments. Determining the probability of default (PD) can be based on the following approaches:
Analyzing historical default frequencies o f a borrower’s homogenous asset classes. Historically, credit analysis was based on subjective analysis, and rating agencies assigned ratings and historical default rates on past observations on an ex post basis (i.e., after an event). Using mathematical and statistical tools. Statistical models are typically used for large portfolios with hundreds or even thousands of positions, which allows for segmentation into different risk classes, measuring risk on an ex ante basis (i.e., before an event). Using a hybrid approach that combines mathematical and judgmental analyses. The mathematical results are generated automatically, which are then corrected using qualitative analysis. Extracting implicit default probabilities from market prices o f publicly listed counterparties.
Default risk is typically measured over one year, although measuring cumulative probabilities of default beyond one year is also important. Shorter exposures are also exposed to default risk. For example, overnight lending will have a non-zero default probability due to unexpected shocks.
Recovery risk measures the risk that the amount recovered, in the event of a default, is less than the full amount that is due. The recovery rate is a conditional metric expressed as a percentage which assumes that default has already occurred. It is the complement to loss given default (LGD) such that the recovery rate equals 1 LGD. The amount of recovery depends on the following factors:
The type o f credit contracts used and the relevant legal system.
General economic conditions. Firms operating in more volatile sectors may see larger
swings in asset values. Covenants. Negative covenants restricting the sale of assets that are important to the borrower should be considered in LGD estimations.
Estimating the recovery rate on ex ante basis is complex due to the difficulty in collecting recovery rate data (including lost data) and problems with uniformity of information. Even when sophisticated techniques allow for the collection of good information, it is challenging
2018 Kaplan, Inc.
Topic 18 Cross Reference to GARP Assigned Reading – De Laurentis et al., Chapter 2
to create a comprehensive model. As a result, less sophisticated models, often using a top- down approach, are commonly used in determining LGD and recovery rates.
Exposure risk measures the amount of risk a firm is exposed to in the event of a default. For term loans, exposure is easily determined. For revolving credit facilities, determining exposure is more challenging since it depends on borrower behavior and external events. In this situation, exposure risk [i.e., exposure at default (EAD)] can be calculated as:
EAD = drawn amount + (limit – drawn amount) x LEQ
where: drawn amount = amount of the credit facility currently used limit = maximum amount granted by a bank to the borrower LEQ = loan equivalency factor (rate of usage of available limit beyond ordinary use)
Other assets (e.g., accounts receivable) pose additional challenges, including events of noncompliance in contractually obligated terms and certain conditions which could alter the amounts due from the borrower. Determining EAD for derivatives contracts is also challenging since market conditions could alter the value of these contracts. In this case, EAD is calculated using stochastic models that forecast future events.
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