Prediction of a financial crisis in Latin American companies using the mixed logistic regression model

Autores
Simões de Araujo, Luiz J.; Giampaoli, Viviana; Tamura, Karin A.; Caro, Norma P.
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.
Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.
Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.
Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.
The development of statistical methods for predicting the financial crisis of a company is a real contribution to scientific research. These methods identify possible adverse financial situations of the companies, through the behavior of their financial indicators. The contribution of this work is to compare the binary classification by different prediction methods of mixed logistic models to predict a future financial crisis in new companies. The results based on an application involving companies from the Argentina, Peru and Chile Stock Exchange showed that all prediction methods were able to predict with high accuracy the financial crisis of the next year.
publishedVersion
Fil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.
Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.
Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.
Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.
Estadística y Probabilidad
Materia
Prediction
Logistic mixed model
Financial crisis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Repositorio
Repositorio Digital Universitario (UNC)
Institución
Universidad Nacional de Córdoba
OAI Identificador
oai:rdu.unc.edu.ar:11086/25188
Acceder
id RDUUNC_1ce9a3a157b8ab4c0a46d624a00518dd
oai_identifier_str oai:rdu.unc.edu.ar:11086/25188
network_acronym_str RDUUNC
repository_id_str 2572
network_name_str Repositorio Digital Universitario (UNC)
spelling Prediction of a financial crisis in Latin American companies using the mixed logistic regression modelSimões de Araujo, Luiz J.Giampaoli, VivianaTamura, Karin A.Caro, Norma P.PredictionLogistic mixed modelFinancial crisisFil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.The development of statistical methods for predicting the financial crisis of a company is a real contribution to scientific research. These methods identify possible adverse financial situations of the companies, through the behavior of their financial indicators. The contribution of this work is to compare the binary classification by different prediction methods of mixed logistic models to predict a future financial crisis in new companies. The results based on an application involving companies from the Argentina, Peru and Chile Stock Exchange showed that all prediction methods were able to predict with high accuracy the financial crisis of the next year.publishedVersionFil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.Estadística y Probabilidad2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf0718-7912http://hdl.handle.net/11086/251880718-7920enginfo:eu-repo/semantics/openAccessreponame:Repositorio Digital Universitario (UNC)instname:Universidad Nacional de Córdobainstacron:UNC2025-10-16T09:29:36Zoai:rdu.unc.edu.ar:11086/25188Institucionalhttps://rdu.unc.edu.ar/Universidad públicaNo correspondehttp://rdu.unc.edu.ar/oai/snrdoca.unc@gmail.comArgentinaNo correspondeNo correspondeNo correspondeopendoar:25722025-10-16 09:29:36.262Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdobafalse
dc.title.none.fl_str_mv Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
title Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
spellingShingle Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
Simões de Araujo, Luiz J.
Prediction
Logistic mixed model
Financial crisis
title_short Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
title_full Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
title_fullStr Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
title_full_unstemmed Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
title_sort Prediction of a financial crisis in Latin American companies using the mixed logistic regression model
dc.creator.none.fl_str_mv Simões de Araujo, Luiz J.
Giampaoli, Viviana
Tamura, Karin A.
Caro, Norma P.
author Simões de Araujo, Luiz J.
author_facet Simões de Araujo, Luiz J.
Giampaoli, Viviana
Tamura, Karin A.
Caro, Norma P.
author_role author
author2 Giampaoli, Viviana
Tamura, Karin A.
Caro, Norma P.
author2_role author
author
author
dc.subject.none.fl_str_mv Prediction
Logistic mixed model
Financial crisis
topic Prediction
Logistic mixed model
Financial crisis
dc.description.none.fl_txt_mv Fil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.
Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.
Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.
Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.
The development of statistical methods for predicting the financial crisis of a company is a real contribution to scientific research. These methods identify possible adverse financial situations of the companies, through the behavior of their financial indicators. The contribution of this work is to compare the binary classification by different prediction methods of mixed logistic models to predict a future financial crisis in new companies. The results based on an application involving companies from the Argentina, Peru and Chile Stock Exchange showed that all prediction methods were able to predict with high accuracy the financial crisis of the next year.
publishedVersion
Fil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.
Fil: Tamura, Karin A. University of São Paulo. Department of Statistics; Brasil.
Fil: Caro, Norma P. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.
Fil: Simões de Araujo, Luiz J. University of São Paulo. Faculty of Economics, Administration and Accounting; Brasil.
Estadística y Probabilidad
description Fil: Giampaoli, Viviana. University of São Paulo. Department of Statistics; Brasil.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 0718-7912
http://hdl.handle.net/11086/25188
0718-7920
identifier_str_mv 0718-7912
0718-7920
url http://hdl.handle.net/11086/25188
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Digital Universitario (UNC)
instname:Universidad Nacional de Córdoba
instacron:UNC
reponame_str Repositorio Digital Universitario (UNC)
collection Repositorio Digital Universitario (UNC)
instname_str Universidad Nacional de Córdoba
instacron_str UNC
institution UNC
repository.name.fl_str_mv Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdoba
repository.mail.fl_str_mv oca.unc@gmail.com
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