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Improved credit rating methods

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.

Research questions

  • How can credit rating methods be improved to lead to better informed decisions more accurate default prediction and reduced credit risk for lenders and bond investors?

Research methods

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:

  • credit risk;
  • capital adequacy; and
  • probabilities of default in extreme market conditions.

Moody’s default and recovery database is used as a key source of ratings data.

Researchers

Funding body

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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