Reconstruction Rating Model of Sovereign Debt by Logical Analysis of Data

Abstract

Sovereign debt ratings provided by rating agencies measure the solvency of a country, as gauged by a lender or an investor. It is an indication of the risk involved in investment and should be determined correctly and in a well-timed manner. The current system is lacking transparency of rating criteria and mechanism. The present study reconstructs sovereign debt ratings through logical analysis of data (LAD), which is based on the theory of Boolean functions. It organizes groups of countries according to 20 World Bank-defined variables for the period 2012-2015. The Fitch Rating Agency, one of the three big global rating agencies, is used as a case study. An approximate algorithm was crucial in exploring the rating method, in correcting the agency's errors, and in determining the estimated rating of otherwise unrated countries. The outcome was a decision tree for each year. Each country was assigned a rating. On average, the algorithm reached almost 98% matched ratings in the training set and was verified by 84% in the test set.