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
- Institución
- Universidad Nacional de Córdoba
- OAI Identificador
- oai:rdu.unc.edu.ar:11086/25188
Ver los metadatos del registro completo
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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:UNC2025-09-29T13:42:20Zoai: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:25722025-09-29 13:42:20.646Repositorio 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 |
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article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
0718-7912 http://hdl.handle.net/11086/25188 0718-7920 |
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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 |
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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) |
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Repositorio Digital Universitario (UNC) |
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Universidad Nacional de Córdoba |
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UNC |
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UNC |
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Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdoba |
repository.mail.fl_str_mv |
oca.unc@gmail.com |
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13.070432 |