Credit Risk Default
Credit Risk
Types of Credit Risk
There are two main types of credit risk:
Credit Spread Risk
Credit spread is the excess return demanded by the market for assuming a certain credit exposure. Credit spread risk is the risk of financial loss owing to changes in the level of credit spreads used in the mark-to-market of a product.
Credit spread risk fits more naturally within a market risk management framework. In order to manage credit spread risk, a firm’s value-at-risk model should take account of value changes caused by the volatility of credit spreads. Since the distribution of credit spreads may not be normal, a standard variance-covariance approach to measuring credit spread risk may be inappropriate. However, the historical simulation approach, which does not make any assumptions about the underlying distribution, used in combination with other techniques, provides a suitable alternative.
Credit spread risk is only exhibited when a mark-to-market accounting policy is applied, such as for portfolios of bonds and credit derivatives. In practice, some types of products, such as corporate or retail loans, are typically accounted for on an accruals basis. A mark-to-market accounting policy would have to be applied to these products in order to recognize the credit spread risk.
Credit Default Risk
Credit default risk is the risk that an obligor is unable to meet its financial obligations. In the event of a default of an obligor, a firm generally incurs a loss equal to the amount owed by the obligor less a recovery amount which the firm recovers as a result of foreclosure, liquidation or restructuring of the defaulted obligor.
All portfolios of exposures exhibit credit default risk, as the default of an obligor results in a loss.
Credit default risk is typically associated with exposures that are more likely to be held to maturity, such as corporate and retail loans and exposures arising from derivative portfolios. Bond markets are generally more liquid than loan markets and therefore bond positions can be adjusted over a shorter time frame. However, where the intention is to maintain a bond portfolio over a longer time frame, even though the individual constituents of the portfolio may change, it is equally important to measure the default risk that is taken by holding the portfolio.
Default Rate Behavior
Equity and bond prices are forward-looking in nature and are formed by investors’ views of the financial prospects of a particular obligor. Hence, they incorporate both the credit quality and the potential credit quality changes of that obligor.
Therefore, the default rate of a particular obligor, inferred from market prices, will vary on a continuous scale and hence can be viewed as a continuous random variable. In modeling credit risk, one is concerned with determining the possible future outcomes over the chosen time horizon.
The process for the default rate can be represented in two different ways:
The above two representations of default rate behaviors are summarized in the following table:
Modeling Approach
Risk Measures
When managing credit risk, there are several measures of risk that are of interest, including the following:
A Portfolio Approach to Managing Credit Risk
Credit risk can be managed through diversification because the number of individual risks in a portfolio of exposures is usually large. Currently, the primary technique for controlling credit risk is the use of limit systems, including individual obligor limits to control the size of exposure, tenor limits to control the maximum maturity of exposures to obligors, rating exposure limits to control the amount of exposure to obligors of certain credit ratings, and concentration limits to control concentrations within countries and industry sectors.
The portfolio risk of a particular exposure is determined by four factors:
(i) The size of the exposure,
(ii) The maturity of the exposure,
(iii) The probability of default of the obligor
(iv) The systematic or concentration risk of the obligor.
Credit limits aim to control risk arising from each of these factors individually. The general effect of this approach, when applied in a well-structured and consistent manner, is to create reasonably well-diversified portfolios. However, these limits do not provide a measure of the diversification and concentration of a portfolio. In order to manage effectively a portfolio of exposures, a means of measuring diversification and concentration has to be developed. An approach that incorporates size, maturity, credit quality and systematic risk into a single portfolio measure is required.
Time Horizon for Credit Risk Modeling
A key decision that has to be made when modeling credit risk is the choice of time horizon. Generally, the time horizon chosen should not be shorter than the time frame over which risk-mitigating actions can be taken.
Tow possible time horizons suggested that can provide management information relevant for credit risk management:
Data inputs to Credit Risk Modeling
Any modeling of credit risk is dependent on certain data requirements being met. The quality of this data will directly affect the accuracy of the measurement of credit risk and therefore any decision to be made using the results should be made only having fully assessed the potential error from uncertainties in the data used.
The inputs used in the model can be:
One of the key limitations in modeling credit risk is the lack of comprehensive default data. Where a firm has its own information that is judged to be relevant to its portfolio, this can be used as the input into the model. Alternatively, conservative assumptions can be used while default data quality is being improved.
Credit Exposures
The exposures arising from separate transactions with an obligor should be aggregated according to the legal corporate structure and taking into account any rights of set-off.
The types of instruments that give rise to credit exposure are including:
For some of these transaction types, it is necessary to make an assumption about the level of exposure in the event of a default:
For example, a financial letter of credit will usually be drawn down prior to default and therefore the exposure at risk should be assumed to be the full nominal amount.
In addition, if a multi-year time horizon is being used, it is important that the changing exposures over time are accurately captured.
Default Rates
A default rate, which represents the likelihood of a default event occurring, should be assigned to each obligor.
This can be achieved in a number of ways, including:
One-year default rates (%) Table
(Carty & Lieberman, 1997, Moody’s Investors Service Global Credit Research)
A credit rating is an opinion of an obligor’s overall financial capacity to meet its financial obligations (i.e. its credit worthiness). This opinion focuses on the obligor’s capacity and willingness to meet its financial commitments as they fall due. An assessment of the nature of a particular obligation, including its seniority in bankruptcy or liquidation, should be performed when considering the recovery rate for an obligor.
Default Rate Volatilities
Published default statistics include average default rates over many years. Actual observed default rates vary from these averages. The amount of variation in default rates about these averages can be described by the volatility (standard deviation) of default rates. As can be seen in the following table, the standard deviation of default rates can be significant compared to actual default rates, reflecting the high fluctuations observed during economic cycles.
Default rate standard deviations (%) Table
(Carty & Lieberman, 1996, Moody’s Investors Service Global Credit Research)
The default rate standard deviations in the above table were calculated over the period from 1970 to 1996 and therefore include the effect of economic cycles.
Recovery Rates
In the event of a default of an obligor, a firm generally incurs a loss equal to the amount owed by the obligor less a recovery amount, which the firm recovers as a result of foreclosure, liquidation or restructuring of the defaulted obligor or the sale of the claim. Recovery rates should take account of the seniority of the obligation and any collateral or security held.
There is also considerable variation for obligations of differing seniority, as can be seen from the standard deviation of the corporate bond and bank loan recovery rates in the table below.
(Historical Default Rates of Corporate Bond Issuers, 1920-1996 (January 1997) Moody’s Investors Service Global Credit Research)
Publicly available recovery rate data indicates that there can be significant variation in the level of loss, given the default of an obligor. Therefore, a careful assessment of recovery rate assumptions is required. Given this uncertainty, stress testing should be performed on the recovery rates in order to calculate the potential loss distributions under different scenarios.
The Random Nature of Defaults and the Impact of the Economy on Default Rates
Credit defaults occur as a sequence of events in such a way that it is not possible to forecast the exact time of occurrence of any one default or the exact total number of defaults. Often, there are background factors that may cause the incidence of default events to be correlated, even though there is no causal link between them.
Also, there is general agreement that the state of the economy in a country has a direct impact on observed default rates. A recent report by Standard and Poor’s stated that “A healthy economy in 1996 contributed to a significant decline in the total number of corporate defaults. Compared to 1995, defaults were reduced by one-half….”
(Standard and Poor’s Ratings Performance 1996, February 1997)
Another report by Moody’s Investors Service stated that “The sources of [default rate volatility] are many, but macroeconomic trends are certainly the most influential factors”.
(Moody’s Investors Service, Corporate Bond Defaults and Default Rates, January 1996)
Furthermore, for each year, different industry sectors will be affected to different degrees by the state of the economy. The magnitude of the impact will be dependent on how sensitive an obligor’s earnings are to various economic factors, such as the growth rate of the economy and the level of interest rates.
