Template-Type: ReDIF-Paper 1.0

Author-Name: Alberto Bernardi
Author-X-Name-First: Alberto
Author-X-Name-Last: Bernardi

Author-Name: Daniela Bragoli
Author-X-Name-First: Daniela
Author-X-Name-Last: Bragoli
Author-Email: daniela.bragoli@unicatt.it
Author-Workplace-Name: Università Cattolica del Sacro Cuore
Author-Workplace-Name: Dipartimento di Matematica per le Scienze economiche, finanziarie ed attuariali, Università Cattolica del Sacro Cuore

Author-Name: Davide Fedreghini
Author-X-Name-First: Davide
Author-X-Name-Last: Fedreghini

Author-Name: Tommaso Ganugi
Author-X-Name-First: Tommaso
Author-X-Name-Last: Ganugi

Author-Name: Giovanni Marseguerra
Author-X-Name-First: Giovanni
Author-X-Name-Last: Marseguerra
Author-Email: giovanni.marseguerra@unicatt.it
Author-Workplace-Name: Università Cattolica del Sacro Cuore
Author-Workplace-Name: Dipartimento di Matematica per le Scienze economiche, finanziarie ed attuariali, Università Cattolica del Sacro Cuore

Title: COVID-19 and firms' financial health in Brescia: A simulation with Machine Learning.

Abstract: COVID-19 has generated an unprecedented shock to the global economy causing both the decrease in demand and supply. The purpose of this paper is to simulate the effect of COVID-19 on firms’ financial statements in Brescia. The shocked information is then fed into two machine learning bankruptcy models with the aim of providing an up-to-date picture of firms’ economic health in one of the most prosperous industrial areas in Italy and Europe.

Length: 35

Creation-Date: 2021-01
File-URL: https://dipartimenti.unicatt.it/dime-dime21_01.pdf
File-Format: Application/pdf
File-Function: First version, 2021
Number: dime21_01
Classification-JEL: G33, C45, C52, R11, L23.
Keywords: COVID-19, financial statements, machine learning, Brescia.
Handle: RePEc:ctc:sdimse:dime21_01