REVERSE-ENGINEERING COUNTRY RISK RATINGS:

A COMBINATORIAL NON-RECURSIVE MODEL

Alex Kogan

Abstract:

The central objective of this paper is to develop a transparent,

consistent, self-contained, and stable country risk rating model, closely

approximating the country risk ratings provided by Standard and Poor's

(S&P). The model should be non-recursive, i.e., it should not rely on the

previous years' S&P ratings. The set of variables selected here includes

not only economic-financial but also political variables. We propose a new

model based on the novel combinatorial-logical technique of Logical Analysis

of Data (which derives a new rating system only from the qualitative

information representing pairwise comparisons of country riskiness). We

also develop a method allowing to derive a rating system that has any desired

level of granularity. The accuracy of the proposed model's predictions,

measured by its correlation coefficients with the S&P ratings, and

confirmed by k-folding cross-validation, exceeds 95%. The stability of the

constructed non-recursive model is shown in three ways: by the correlation

of the predictions with those of other agencies (Moody's and The Institutional

Investor), by predicting 1999 ratings using the non-recursive model

derived from the 1998 dataset applied to the 1999 data, and by successfully

predicting the ratings of several previously non-rated countries. This

study provides new insights on the importance of variables by supporting the

necessity of including in the analysis, in addition to economic variables,

also political variables (in particular "political stability"), and by

identifying "financial depth and efficiency" as a new critical factor in

assessing country risk.