C04 EXTERNAL & INTERNAL RATINGS

EXTERNAL CREDIT RATINGS #

External rating scales are designed to convey information about either a specific instrument, called an issue-specific credit rating, or information about the entity that issued the instrument, which is called an issuer credit rating, or both. The ratings are typically one-dimensional, and the ratings scale goes from the highest rating to the lowest in uniform increments.

The ratings process usually consists of the following steps:

1. Conducting qualitative analysis.
2. Conducting quantitative analysis.
3. Meeting with the firm’s management.
4. Meeting of the committee in the rating agency assigned to rating the firm.
5. Notifying the rated firm of the assigned rating.
6. Opportunity for the firm to appeal or offer new information.
7. Disseminating the rating to the public via the news media.

RATING TRANSITION MATRIX #

Researchers have composed tables (known as a transition matrices) that show the frequency of default, as a percent, over given time horizons for bonds that began the time horizon with a given rating. These tables use historical data to report that for bonds that began a 3-year period with an Aa rating, for example, a certain percent defaulted during the five years. These tables demonstrate that the higher the credit rating, the lower the default frequency.

EVOLUTION OF INTERNAL CREDIT RATINGS #

Previous internal credit ratings approaches were very simplistic, as they often just identified a company as being either a good or a bad borrower. This process lacked the ability to assign unique interest rates based on individual probability of default (PD) and loss given default (LGD).

Two key factors have contributed to the increase in sophistication of internal credit ratings: the growing use of external credit rating agency language in the financial markets and the encouragement of Basel II rules to refine the approach for calculating credit risk capital requirements. Internal credit ratings models continue to improve, but key issues still exist regarding objectivity, data quality, time horizon, and consistency with external ratings.

IMPACT OF TIME HORIZON, ECONOMIC CYCLE, INDUSTRY, AND GEOGRAPHY ON EXTERNAL RATINGS #

Ratings agencies determine the external rating of a firm or bond using current information with the goal of indicating the probability of future events such as default and/or loss. The probability of default given any rating at the beginning of a cycle increases with the horizon. The increase in the default rates, or cumulative default rate, is much more dramatic for non-investment grade bonds. In addition to the condition of the firm, forecasted events in the horizon will affect the probabilities. The most notable events are the economic and industrial cycles. Since the rating should apply to a long horizon, in many cases, ratings agencies try to give a rating that incorporates the effect of an average cycle. This practice leads to the ratings being relatively stable over  

Ratings agencies apply their ratings to different types of firms around the world, and the ratings may be interpreted differently given a specific industry and geographic location.

IMPACT OF RATING CHANGES ON BOND & STOCK PRICES #

 IMPACT ON BOND:

A rating downgrade is likely to make the bond price decrease (stronger evidence).

A rating upgrade is likely to make the bond price increase (weaker evidence).

IMPACT ON STOCK PRICES:

For stocks, the change in bond ratings has an even more asymmetric effect on the stock prices than it does on bond prices:

A rating downgrade is likely to lead to a stock price decrease (moderate evidence).

A rating upgrade is somewhat likely to lead to a stock price increase (evidence is mixed).

EVOLUTION OF INTERNAL CREDIT RATINGS #

Previous internal credit ratings approaches were very simplistic, as they often just identified a company as being either a good or a bad borrower. This process lacked the ability to assign unique interest rates based on individual probability of default (PD) and loss given default (LGD).

Two key factors have contributed to the increase in sophistication of internal credit ratings: the growing use of external credit rating agency language in the financial markets and the encouragement of Basel II rules to refine the approach for calculating credit risk capital requirements. Internal credit ratings models continue to improve, but key issues still exist regarding objectivity, data quality, time horizon, and consistency with external ratings.

INTERNAL CREDIT RATINGS #

1. AT-THE-POINT APPROACH: This approach’s goal is to predict the credit quality over a relatively short horizon of a few months or, more generally, a year. Banks use this approach and employ quantitative models to determine the credit score.
2. THROUGH-THE-CYCLE APPROACH: It focuses on a longer time horizon and includes the effects of forecasted cycles. The approach uses more qualitative assessments. Given the stability of the ratings over an economic cycle, when using through- the-cycle approaches, high-rated firms may be underrated during growth periods and overrated during the decline of a cycle.

Internal ratings can have a procyclical effect on the economy since banks often change ratings with a lag with respect to the change in the economy. Thus, after the economic trough has been reached, it is possible that a bank may downgrade a company poised for recovery with the use of additional credit from the bank.

In order to build an internal rating system, banks should create ratings that resemble those set by ratings agencies. However, before banks can link default probabilities to internal ratings, it is necessary to backtest the current internal rating system.

BIASES THAT MAY AFFECT A RATING SYSTEM #

An internal rating system may be biased by several factors. The following list identifies the main factors:

1.Time horizon bias: mixing ratings from different approaches to score a company

2. Homogeneity bias: inability to maintain consistent ratings methods.
3. Principal/agent bias: moral hazard could result if bank employees do not act in the interest of management.
4. Information bias: ratings assigned based on insufficient information.
5. Criteria bias: allocation of ratings is based on unstable criteria.
6. Scale bias: ratings may be unstable over time.
7. Back testing bias: incorrectly linking rating system to default rates.
8. Distribution bias: using an incorrect distribution to model probability of default.