This project seeks to develop improved credit ratings methods which lead to better informed decisions, more accurate default prediction and reduced credit risk for lenders and bond investors.
We hypothesise that existing credit rating methods do not adequately rate credit risk in dynamic circumstances.
The project uses market-based models such as Moody’s KMV, and external ratings based methods. Innovations include combining these models, as well as enhancing them to include extreme risk measures such as Conditional Value at Risk (CvaR).
The models are designed to more accurately measure and predict:
Moody’s default and recovery database is used as a key source of ratings data.
This project was initially funded through a Faculty of Business and Law, Strategic Research Grant and is now an ongoing project.
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