Mod 23: Assessment of credit risks Flashcards
Outline two (potential) main components of credit risk ©
Components of credit risk
Credit risk has two main components:
1.default risk, which may be decomposed into
- the probability of default (ie the chance of a default event occurring) in respect of each counterparty
- the loss on default (which, in respect of each counterparty, is a function of the exposure and the likely recoveries in the event of default)
- the level and nature of interactions between the various credit exposures and other (non-credit) risks in a portfolio
2.credit spread risk−
-credit spread risk relates to the uncertainty in the difference between the yield on a risky and a risk-free security
-excluded by some (Sweeting includes in market risk) ©
State the conditions under which default might be deemed to have occurred
Conditions under which default might be deemed to have occurred
1. a payment due is missed
2. a financial ratio falls above or below a certain
3. level legal proceedings start against the credit issuer
4. the present value of assets falls below that of liabilities due to economic factors
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Outline the problems in assessing expected loss on default ©
Difficulties in assessing expected loss on default
- The exposure may be unclear, particularly for derivatives whose values fluctuate with market movements.
- Although the exposure at an exact point in time may be known (the market value), it is often unsatisfactory to treat this as the full extent of the exposure to the counterparty. It may be necessary to make estimates of average exposure for derivatives, or indeed to model the possible future exposure using a Monte Carlo model for more complex exposures such as swaps.
- Loss is calculated net of recoveries, which can take a lengthy time to obtain, and usually require costly legal proceedings – all of which is uncertain.
- Any reduction in uncertainty due to credit enhancement (eg collateral from counterparties, or third-party guarantees) need to be assessed.
State the general methods companies use to minimise credit risk ©
Methods of minimising credit risk
1. avoid bad risks in the first place!
2. diversify credit exposure across a number of counterparties
3. monitor exposure regularly
4. take immediate action when default occurs ©
List sources of information to assess credit risk ©
Sources of information to assess credit risk
Information to assess credit risk may be sought from:
1. credit rating agencies, eg via interviews
2. the counterparty, eg via questionnaires
3. publicly available data, eg information disclosed under Basel disclosure rules or stock exchange listing rules
4. proprietary databases, eg Experian
There is a trade-off between the cost of obtaining more information and the benefit it brings in terms of improved analysis.
Describe the main types of credit-risk models ©
Main groups of credit-risk models
1. quantitative credit models: eg S&P rating of ERM capability
2. qualitative credit models,
1. credit-scoring models of default probability given fundamental info on the counterparty, eg empirical models, expert models
2. structural (or firm-value) models of default probability based on market data, eg Merton, KMV
3. reduced-form models, which model default as a statistical process that typically depends upon economic variables, eg credit-migration models
4. credit exposure models, used in more complex circumstances, eg using MC simulation to estimate credit exposures
5. credit portfolio models, used to estimate credit exposure across many counterparties allowing for diversification / aggregation
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Outline the qualitative approach to modelling credit risk
Qualitative credit risk modelling
Subjective assessments of both default and credit spread risk are based on relevant factors, such as:
1. the nature of contractual obligations, eg seniority of the debt the
2. level and nature of any security, eg collateral, parent guarantees
3. the nature of the borrower, eg industry sector economic indicators, eg inflation rates
4. financial ratios ̧ eg gearing
5. face-to-face meetings with the credit issuer and/or counterparty.
In respect of the chosen time horizon, the assessment will ultimately consider:
1. the risk of default
2. the perceived creditworthiness of the counterparty
3. how the risk(s) may change over time.
Outline the main advantages and disadvantages of qualitative models
Advantages and disadvantages of qualitative models
Adv:
a wide range of factors can be incorporated into the assessment (beyond purely quantitative factors)
DisAdv:
- excessive subjectivity and the presence of bias
- a lack of consistency between ratings (between sectors, between analysts, etc)
- the changing meaning of subjective ratings, eg over the economic cycle
- ratings may fail to respond to changes, eg in the economic cycle or in circumstances of the counterparty, there is often a reluctance to change a credit rating
Outline the Merton model ©
see 746
Outline three advantages of the Merton model ©
Advantages of the Merton model
1. It is mathematically tractable, using results from Black-Scholes option pricing.
2. It results in an intuitive, economic explanation for the probability of default, which is based on the structure of a company and changes in its value.
3. It can be used to estimate an appropriate credit spread for a bond, even when the bond is unquoted and/or unrated.
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Outline the drawbacks associated with the assumptions involved in the Merton approach
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Drawbacks associated with the assumptions in the Merton approach
Unrealistic assumptions:
1. markets are frictionless (ie no transaction costs) with continuous trading
2. the risk-free rate is deterministic and constant for borrowers / lenders
3. Xt follows a log-normal random walk with fixed rate of growth and fixed volatility (ie independent of the company’s financial structure, eg level of gearing)
4. Xt is an observable traded security (which is rarely correct) the 5.bond is a zero-coupon bond with only one default opportunity
default results in liquidation – however, default can mean a variety of things other than liquidation in real life
6. sigmaX is observable (which is normally impossible) ©
Outline the KMV model
The KMV model The KMV model assumes a company will default at the first instance that
Xt
falls below B as determined from term structure of all the company’s liabilities (eg B is often taken as the liabilities falling within one year).
The distance to default (DD ) is the number of standard deviations that the
company’s assets have to fall in value before they breach the threshold B .
see 752
Using empirical data on company defaults and how these defaults link with the DD , the model is used to estimate the likelihood of default for any given company over the coming year.
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State the advantages of the KMV model over the Merton model ©
The relative advantages of the KMV model over the Merton model
- coupon-paying bonds can be modelled
- more complex liability structures can be accommodated as the system uses the average coupon and the overall gearing level
- Xt is not assumed to be observable, and is derived from the value of the company’s equity shares
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Outline the credit-migration modelling process and its assumptions
Credit-migration models
Credit-migration models estimate how a credit rating might change over time. The modelling process generally has three steps:
1. Historical data is used to determine 1-year re-rating probabilities which are then recorded in rating transition probability matrices.
2. These are applied (repeatedly) to a counterparty’s current rating to estimate the likelihood of each possible rating in each future year.
3. Then using the probability of default for a company of a given rating, the model estimates the chance of default in each future year.
This relies on:
1. the migration process following a time-homogeneous Markov chain
2. there being a credit rating that reflects the company’s default likelihood ‘through the business cycle’ (rather than reflecting the default chance in the current economic environment).
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Outline the disadvantages (both technical and practical) of credit-migration models
Disadvantages of credit-migration models
1. the time-homogeneity assumption has been criticised using empirical evidence and appears unintuitive
2. the approach assumes that the likelihood of default can be determined solely by the company’s credit rating
3. the credit rating reflects the ‘average’ default probability over an economic cycle and can be slow to adjust to a changing environment
4. a low number of distinct credit ratings results in a low level of granularity in the default estimates
5. rankings by the different credit rating agencies do not always coincide
6. not all organisations have obtained a (costly) credit rating
7. ratings are sometimes unavailable (withdrawn)
8. the models assume that default probabilities in each future year can be estimated
9. he models rely on considerable data collected over a long time period
