Faculty & Research

This talk comprises two parts. First, the forward intensity method for corporate default predictions proposed by Duan, Sun and Wang (2011) will be introduced with discussions on its conceptual foundation, econometric formulation, implementation issues and empirical findings on the US data. The talk will also touch upon the role of momentum in default prediction and a useful distance-to-default treatment for financial firms if one wants to include them in the sample. The forward intensity method powers the default prediction system of the non-profit Credit Research Initiative (CRI) by the Risk Management Institute of National University Singapore. The CRI currently produces daily updated default predictions, from one month to two years ahead, for about 30,000 exchange-listed firms in 30 economies in Asia, North America and Europe. In the second part of the talk, I will show how one can utilize the freely accessible CRI infrastructure for credit portfolio management. Since the forward intensity approach considers all obligors jointly and dynamically, it naturally forms a bottom-up approach to modeling credit portfolios. An example will be used to demonstrate this application.