Modeling country risk ratings using partial orders

P. L. Hammer, A. Kogan, M. A. Lejeune

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

In order to evaluate the creditworthiness of various countries, a learning model is induced from the 1998 Standard and Poor's country risk ratings, using the 1998 values of nine economic and three political indicators. This learning model allows the construction of a partially ordered set describing the relative superiority of countries on the basis of their creditworthiness, and it is shown that the Condorcet linear extensions of this poset match closely the S&P ratings. Moreover, the ratings derived from the model correlate highly with those 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 of the (few) discrepancies between the constructed poset and S&P's initial ratings.

Original languageEnglish (US)
Pages (from-to)836-859
Number of pages24
JournalEuropean Journal of Operational Research
Volume175
Issue number2
DOIs
StatePublished - Dec 1 2006

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Keywords

  • Country risk ratings
  • Cross-validation
  • Data mining
  • LAD
  • Partially ordered set

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