Rating Firms and Sensitivity Analysis

Journal of the Operational Research Society (2019), https://doi.org/10.1080/01605682.2019.1650626

36 Pages Posted: 21 Jul 2019 Last revised: 30 Apr 2020

See all articles by Carlo Alberto Magni

Carlo Alberto Magni

Università degli studi di Modena e Reggio Emilia (UNIMORE) - School of Doctorate E4E (Engineering for Economics-Economics for Engineering)

Stefano Malagoli

Kaleidos Corporate Finance

Andrea Marchioni

Università degli studi di Modena e Reggio Emilia (UNIMORE) - Dipartimento di Economia Marco Biagi di Modena

Giovanni Mastroleo

University of Salento - Department of Economics and Mathematics and Statistics

Date Written: July 20, 2019

Abstract

This paper introduces a model for rating a firm's default risk based on fuzzy logic and expert system and an associated model of sensitivity analysis (SA) for managerial purposes. The rating model automatically replicates the evaluation process of default risk performed by human experts. It makes use of a modular approach based on rules blocks and conditional implications. The SA model investigates the change in the firm's default risk under changes in the model inputs and employs recent results in the engineering literature of Sensitivity Analysis. In particular, it (i) allows the decomposition of the historical variation of default risk, (ii) identifies the most relevant parameters for the risk variation, and (iii) suggests managerial actions to be undertaken for improving the firm's rating.

Keywords: credit rating, default risk, fuzzy logic, fuzzy expert system, sensitivity analysis

JEL Classification: G00, G30, G32, G33, C67, D81

Suggested Citation

Magni, Carlo Alberto and Malagoli, Stefano and Marchioni, Andrea and Mastroleo, Giovanni, Rating Firms and Sensitivity Analysis (July 20, 2019). Journal of the Operational Research Society (2019), https://doi.org/10.1080/01605682.2019.1650626, Available at SSRN: https://ssrn.com/abstract=3423440

Carlo Alberto Magni (Contact Author)

Università degli studi di Modena e Reggio Emilia (UNIMORE) - School of Doctorate E4E (Engineering for Economics-Economics for Engineering) ( email )

Italy

Stefano Malagoli

Kaleidos Corporate Finance ( email )

Piazza San Sepolcro 1
20123 Milano
Italy

Andrea Marchioni

Università degli studi di Modena e Reggio Emilia (UNIMORE) - Dipartimento di Economia Marco Biagi di Modena ( email )

Viale Berengario 52
Modena, Modena 41121
Italy

Giovanni Mastroleo

University of Salento - Department of Economics and Mathematics and Statistics ( email )

Piazza Tancredi, n7
Lecce, 73100
Italy

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
34
Abstract Views
439
PlumX Metrics