Volume 50, Number 4-5, October-December 2016
Special issue - Advanced Optimization Approaches and Modern OR-Applications
|Page(s)||749 - 765|
|Published online||03 November 2016|
Automated Credit Rating Prediction in a competitive framework
1 Operations Research and Business
Informatics Saarland University, 66123
email@example.com, firstname.lastname@example.org, email@example.com
2 Luxembourg Institute of Science and Technology, 4362 Esch-sur-Alzette, Luxembourg.
3 University of Cape Town, Department of Finance and Tax, Cape Town, South Africa.
Accepted: 23 April 2016
Automated credit rating prediction (ACRP) algorithms are used to predict the ratings of bonds without having to trust one rating agency, like Moody’s, Fitch or S&P. Nevertheless, for the moment, the accuracy of ACRP algorithms is investigated by empirical tests. In this paper, the framework for a competitive analysis is set and afterwards in this framework, the definition of competitive ACRP algorithms and its demonstration is given. In this way, for a competitive ACRP algorithm, a worst-case guarantee concerning the misclassification error is offered. Furthermore, several ACRP algorithms from the literature are compared according their competitiveness.
Mathematics Subject Classification: 49-02
Key words: Automated credit rating prediction / competitive analysis / financial bond credit rating
© EDP Sciences, ROADEF, SMAI 2016
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