Friday, October 7, 2005
1:30 pm Posner Hall 151
Miguel Lejeune
Visiting Assistant Professor, Tepper School of Business
Derivation of Country Risk Rating Systems Using Logical Analysis of Data
In order to evaluate the creditworthiness of countries, a learning model is induced from Standard & Poors country risk ratings. The learning model is obtained using the combinatoriallogical technique of Logical Analysis (LAD), and allows the construction of a partially ordered set describing the relative superiority of countries on the basis of their creditworthiness. It is shown that the Condorcet linear extensions of this poset match closely S&Ps ratings. The rating system derived from the model is transparent, self-contained, provides stable country risk rating systems, and correlate highly with the ratings of other rating agencies. The model is shown to provide excellent ratings even when applied to the following years data or to the ratings of previously unrated countries. Rating changes implemented by S&P in subsequent years resolved most discrepancies between the constructed poset and S&Ps initial ratings.
