التفاصيل البيبلوغرافية
| العنوان: |
MURAME parameter setting for creditworthiness evaluation: data-driven optimization |
| المؤلفون: |
Marco Corazza, Giovanni Fasano, Stefania Funari, Riccardo Gusso |
| المصدر: |
Springer;Associazione per la Matematica, Decisions in Economics and Finance. 44(1):295-339 |
| سنة النشر: |
2021 |
| الوصف: |
In this paper, we amend a multi-criteria methodology known as MURAME, to evaluate the creditworthiness of a large sample of Italian Small and Medium-sized Enterprises, using as input their balance sheet data. This methodology produces results in terms of scoring and of classification into homogeneous rating classes. A distinctive goal of this paper is to consider a preference disaggregation method to endogenously determine some parameters of MURAME, by solving a nonsmooth constrained optimization problem. Because of the complexity of the involved mathematical programming problem, for its solution we use an evolutionary metaheuristic, coupled with a specific efficient initialization. This is combined with an unconstrained reformulation of the problem, which provides a reasonable compromise between the quality of the solution and the computational burden. An extensive numerical experience is reported, comparing an exogenous choice of MURAME parameters with our approach. |
| نوع الوثيقة: |
redif-article |
| اللغة: |
English |
| DOI: |
10.1007/s10203-021-00322 |
| الإتاحة: |
https://ideas.repec.org/a/spr/decfin/v44y2021i1d10.1007_s10203-021-00322-1.html |
| رقم الأكسشن: |
edsrep.a.spr.decfin.v44y2021i1d10.1007.s10203.021.00322.1 |
| قاعدة البيانات: |
RePEc |
