A multiple criteria sorting methodology with multiple classifi cation criteria and an application to country risk evaluation

Abstract

In this paper, we propose an extension of the standard UTADIS methodology, an approach that originates from multicriteria decision aid (MCDA) for sorting problems, such that it can handle more than one classification criteria simultaneously which possibly involves different predefined classes for alternatives. Moreover, we test the classification ability of the standard UTADIS methodology using the out-of-classification criterion approach, a new variant of the studies comprising out-of-time and out-of-sample testing methodologies. Results obtained in out-of-classification criterion testing are then compared with the classification ability of the Multiple Classification Criteria UTADIS (MCC UTADIS). Finally, an application to country risk evaluation is performed. In this application, classifications of two credit rating agencies, Standard & Poor's and Moody's, are taken as two different classification criteria. Moreover, robustness of MCC UTADIS method is tested through using several data sets. Results indicate that MCC UTADIS involving more than one classification criteria performs very close to standard UTADIS with single classification criterion and performs better than the out-of-classification criterion tests. These results emphasize both the sensitivity of UTADIS models to the classification criteria and the importance of using a multiple classification criteria approach.

Keywords

• Operations research
• optimization
• multiple criteria decision analysis
• country risk