Autori
Piras, Nicola
Supino, Enrico

Titolo
Le performance dei modelli di credit scoring in contesti di forte instabilità macroeconomica: il ruolo delle Reti Neurali Artificiali
Periodico
MC
Anno: 2022 - Fascicolo: 2 - Pagina iniziale: 41 - Pagina finale: 61

The study addresses the problem related to the performance of the tools for forecasting corporate crises in periods characterized by strong macroeconomic instability (financial crises, pandemics, wars, etc.). The results obtained show how the performances of the models decrease over time and how, in a period characterized by strong macroeconomic instability, more evident drops in performance are observed. Particularly, with reference to the hotel sector in Italy, in correspondence with and immediately after the financial crisis of 2008, it emerges that artificial neural networks produce more precise and less volatile predictions than the classical models used in the literature (linear discriminant analysis and logistic regression).



SICI: 2239-0391(2022)2<41:LPDMDC>2.0.ZU;2-Y
Testo completo: http://www.francoangeli.it/riviste/Scheda_Rivista.aspx?IDArticolo=71300&Tipo=Articolo PDF

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