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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Estimating the Probability of a Corporate Credit Rating Downgrade |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2018 |
| Abstract Text | Although this thesis begins with discussing possible factors explaining credit rating downgrades that are identified by a univariate analysis based on a fixed effects logistic regression on constructed panel data, the main focus lies on the development of random effects logistic regression models to estimate downgrade probabilities for different time horizons. The final models include macroeconomic factors, aspects of corporate governance, accounting and equity market information, an issuer’s rating history and is also dependent on an issuer’s sector classification and its current credit rating. While the estimated models allow to quantify downgrade probabilities, their predictive powers are limited. |
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