Name
Abstract | ||
|---|---|---|
Rating models are widely used by credit institutions to obtain estimates for the probabilities of default for their clients (firms, organizations, individuals) and to assess the risk of credit portfolios. Several statistical and data mining methods are used to develop such models. In this article, the potential of an outranking multicriteria decision-aiding approach is explored. An evolutionary algorithm is used to fit a credit rating model on the basis of the ELimination Et Choix Traduisant la REalite trichotomique method. The methodology is applied to a large sample of Greek firms. The results indicate that outranking models are well suited to credit rating, providing good classification results and useful insight on the relative importance of the evaluation criteria. [Submitted: June 22, 2010. Revisions received: November 3, 2010; January 10, 2011. Accepted: January 12, 2011.] |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1111/j.1540-5915.2011.00328.x | DECISION SCIENCES |
Keywords | Field | DocType |
risk management | Economics,Actuarial science,Evolutionary algorithm,Credit rating,Risk management,Financial distress | Journal |
Volume | Issue | ISSN |
42 | 3 | 0011-7315 |
Citations | PageRank | References |
13 | 0.55 | 21 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Doumpos | 1 | 757 | 51.71 |
| Constantin Zopounidis | 2 | 1066 | 90.47 |