Week 4: Default Probabilities – Part 1

Week 4: Default Probabilities – Part 1

“Introduction … Introduction and Overview … External Credit Ratings … Internal Ratings and Recovery Rates”
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Summaries

  • Week 4: Default Probabilities - Part 1 > Lesson 1: Introduction and Overview > Video Lesson
  • Week 4: Default Probabilities - Part 1 > Lesson 2: External Credit Ratings > Video Lesson
  • Week 4: Default Probabilities - Part 1 > Lesson 3: Internal Ratings and Recovery Rates > Video Lesson
  • Week 4: Default Probabilities - Part 1 > Summary > Video

Week 4: Default Probabilities – Part 1 > Lesson 1: Introduction and Overview > Video Lesson

  • Simplifying a little bit, we can make use of tools belonging to two important classes: ratings and default models.
  • Within the ratings’ class, we can make a distinction between external and internal ratings.
  • External ratings are ratings – credit ratings to be more precise – that we obtain from third parties, typically rating agencies, such as Moody’s, Fitch and Standard and Poor’s.
  • If we consider the other class, the one of default models, we can make a clear distinction between structural and non-structural models of default.
  • A structural model of default is a model in which default happens when the assets of a company reach a sufficiently low level with respect to liabilities.
  • This family of models include some of the most important models in credit risk management, such as Merton’s model, and proprietary models like Moody’s KMV and JP Morgan’s CreditMetrics.
  • Non-structural models of default include mixture models and other rather sophisticated approaches.
  • It is worth noticing that the great majority of methods and models we will consider belong to the internal-rating based approach of Basel II and III.
  • Always speaking about PDs, we will also deal with some tools like CDS and credit spreads, and we will see how we can use them to estimate the probability of default of a counterparty.

Week 4: Default Probabilities – Part 1 > Lesson 2: External Credit Ratings > Video Lesson

  • Hi. How often have you read or heard something like “this company is AAA?” Or “That country has been downgraded from AAA to AA “? Yes, the topic of today are credit ratings.
  • At the end of this class, you will be able to understand and use credit ratings, at least basically.
  • The goal of a credit rating is to provide reliable information about credit quality, about the credit worthiness of a counterparty.
  • When using credit ratings, the implicit assumption is that the information provided by a rating fully determines the probability of default of our counterparty.

Week 4: Default Probabilities – Part 1 > Lesson 3: Internal Ratings and Recovery Rates > Video Lesson

  • The ratings published by rating agencies are only available for large companies, whose bonds are traded on the market.
  • So what happens in those cases? The solution is represented by internal ratings.
  • The internal-rating based approach of Basel II and III allows banks to use internal methods to determine the probability of default of a counterparty.
  • Therefore most banks have their own procedures to assess the creditworthiness of their corporate and retail clients, especially when external credit ratings are not available.
  • The prototype of internal rating methods is represented by Altman’s Z-score.
  • Introduced in 1968, the Z-score is a financial distress index, extremely important in fundamental analysis.
  • There are different versions of Altman’s Z-score, depending on the type of company/client under scrutiny: large company, small company, manufacturing company, and so on.
  • For publicly traded manufacturing companies, the Z-score is obtained with the present equation.
  • By plugging in the values of the balance sheet ratios, we get a number: the Z-score.
  • This number must be compared with some specific thresholds, which are obtained by analyzing historical data about the financial distress and the default of companies.
  • If the Z-score is between 1.8 and 2.7, default is definitely possible.
  • Most of these are just modifications of Altman’s Z-score, or they are obtained using similar techniques.
  • As we can expect, similar methods are also used by rating agencies to assign a rating to bonds, especially when they first appear on the market.
  • The recovery rate is “the amount of credit recovered through foreclosure or bankruptcy procedures in event of a default, expressed as a percentage of face value”.
  • The average recovery rate for bonds is around 35-40%. For loans and mortgages with first lien on assets, it is usually around 65%. Recovery rates are negatively correlated with default rates on the market.

Week 4: Default Probabilities – Part 1 > Summary > Video

  • When you listen to the word “ratings”, most people refer to external ratings, that is those ratings that are given by rating agencies, such as Fitch, for example.
  • On the contrary, we always say “internal ratings”, to indicate those ratings that are not acquired from rating agencies.
  • For what concerns external ratings, we have said that every rating agency has its own ratings scale, but that the ratings of the top three agencies are considered comparable.
  • Ratings fully determine the probability of default of a counterparty.
  • We have seen that, even if ratings are always related to a specific bond issue , most of the times all the bonds issued by the same company have the same rating.
  • We have also seen that rating agencies provide transition matrices, giving information on the possibility that – say – a AAA bond is downgraded to AA, and tables containing the cumulative probability of default for every rating class.
  • Internal ratings are computed by banks and companies themselves.

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