Practice Question Set: De Laurentis, Chapter 3: Ratings Assignment Methodologies

De Laurentis, Chapter 3: Ratings Assignment Methodologies Practice Question set contains 23 pages covering the following learning objectives:

* Explain the key features of a good rating system.
* Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default.
* Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, marginal probability of default, and annualized default rate.
* Describe rating agencies’ assignment methodologies for issue and issuer ratings.
* Describe the relationship between borrower rating and probability of default.
* Compare agencies’ ratings to internal experts-based rating systems.
* Distinguish between the structural approaches and the reduced-form approaches to predicting default.
* Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model.
* Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit quality.
* Describe the application of a logistic regression model to estimate default probability.
* Define and interpret cluster analysis and principal component analysis.
* Describe the use of a cash flow simulation model in assigning rating and default probability, and explain the limitations of the model.
* Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define their strengths and weaknesses.
* Describe the role and management of qualitative information in assessing probability of default.

We have also provided individual links for each question to their respective forum discussion.

Download Sample

Shop Courses