The classifications of risk made by international rating agencies aim at guiding investors when it comes to the capacity and disposition of the evaluated countries to honor their public debt commitments. In this study, the analysis of economic variables of sovereign rating, in a context of vagueness and uncertainty, leads the inference of patterns (multi-criteria rules) by following the Dominance-based Rough Set Approach (DRSA). The discovery of patterns in data may be useful for subsidizing foreign investment decisions in countries; and this knowledge base may be used in rule-based expert systems (learning from training examples).The present study seeks to complement the analysis produced by an international credit rating agency, Standard & Poor’s (S&P), for the year 2018.

Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Artificial Intelligence, Software Development