DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY

Descripción del Articulo

The companies increasingly interact with clients and providers. This situation requires adequate risk ma-nagement to prevent situations of financial distress. A company is technically insolvent when it has enough cash to make immediate payments. Therefore, one of the points to study is the financial...

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Detalles Bibliográficos
Autores: Aldazábal Contreras, Janet Cecibel, Napán Vera, Alberto Fernando
Formato: artículo
Fecha de Publicación:2014
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/11035
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/11035
Nivel de acceso:acceso abierto
Materia:Bankruptcy
prediction models
ratio
Multiple Dis-criminant Analysis
Altman
Quiebra
modelos de predicción
Análisis Discriminante Múltiple
Altman.
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spelling DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCYANÁLISIS DISCRIMINANTE APLICADO A MODELOS DE PREDICCIÓN DE QUIEBRAAldazábal Contreras, Janet CecibelNapán Vera, Alberto FernandoBankruptcyprediction modelsratioMultiple Dis-criminant AnalysisAltmanQuiebramodelos de predicciónratioAnálisis Discriminante MúltipleAltman.The companies increasingly interact with clients and providers. This situation requires adequate risk ma-nagement to prevent situations of financial distress. A company is technically insolvent when it has enough cash to make immediate payments. Therefore, one of the points to study is the financial solvency and risk to the bankruptcy of its customer base. To this end, there are techniques to measure the possibility of insolvency of a company. The most reliable is the Altman Z model, which is based on the statistical technique of Multiple Discriminant Analysis. This model uses financial ratios to determine the financial risk and predict whether a company is healthy from a financial point of view, or is on its way to become insolvent. The results found by Altman and revision of the original model proposed by him is presented.Las empresas interactúan cada vez más con clientes yproveedores. Esta situación hace necesaria una adecuadagestión del riesgo para prevenir situaciones deinsolvencia financiera. Una empresa es técnicamenteinsolvente cuando no tiene efectivo suficiente paraefectuar sus pagos inmediatos. Por lo tanto, uno de lospuntos a estudiar es la solvencia financiera y el riesgo ala quiebra de su cartera de clientes. Para este fin, existentécnicas que permiten medir esta posibilidad de insolvenciade una empresa. Entre las más confiables está elmodelo Z de Altman, el cual está basado en la técnicaestadística del Análisis Discriminante Múltiple. Estemodelo emplea ratios financieros para determinar elriesgo financiero y predecir si una empresa es saludabledesde el punto de vista financiero o se encuentra encamino a ser insolvente. Se presentan los resultadoshallados por Altman y la revisión del modelo originalplanteado por él.Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables2014-12-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/1103510.15381/quipu.v22i42.11035Quipukamayoc; Vol. 22 Núm. 42 (2014); 53-59Quipukamayoc; Vol. 22 No. 42 (2014); 53-591609-81961560-9103reponame:Revistas - Universidad Nacional Mayor de San Marcosinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspahttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/11035/9925Derechos de autor 2014 Janet Cecibel Aldazábal Contreras, Alberto Fernando Napán Verahttps://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessoai:ojs.csi.unmsm:article/110352020-05-30T21:22:03Z
dc.title.none.fl_str_mv DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
ANÁLISIS DISCRIMINANTE APLICADO A MODELOS DE PREDICCIÓN DE QUIEBRA
title DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
spellingShingle DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
Aldazábal Contreras, Janet Cecibel
Bankruptcy
prediction models
ratio
Multiple Dis-criminant Analysis
Altman
Quiebra
modelos de predicción
ratio
Análisis Discriminante Múltiple
Altman.
title_short DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
title_full DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
title_fullStr DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
title_full_unstemmed DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
title_sort DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
dc.creator.none.fl_str_mv Aldazábal Contreras, Janet Cecibel
Napán Vera, Alberto Fernando
author Aldazábal Contreras, Janet Cecibel
author_facet Aldazábal Contreras, Janet Cecibel
Napán Vera, Alberto Fernando
author_role author
author2 Napán Vera, Alberto Fernando
author2_role author
dc.subject.none.fl_str_mv Bankruptcy
prediction models
ratio
Multiple Dis-criminant Analysis
Altman
Quiebra
modelos de predicción
ratio
Análisis Discriminante Múltiple
Altman.
topic Bankruptcy
prediction models
ratio
Multiple Dis-criminant Analysis
Altman
Quiebra
modelos de predicción
ratio
Análisis Discriminante Múltiple
Altman.
description The companies increasingly interact with clients and providers. This situation requires adequate risk ma-nagement to prevent situations of financial distress. A company is technically insolvent when it has enough cash to make immediate payments. Therefore, one of the points to study is the financial solvency and risk to the bankruptcy of its customer base. To this end, there are techniques to measure the possibility of insolvency of a company. The most reliable is the Altman Z model, which is based on the statistical technique of Multiple Discriminant Analysis. This model uses financial ratios to determine the financial risk and predict whether a company is healthy from a financial point of view, or is on its way to become insolvent. The results found by Altman and revision of the original model proposed by him is presented.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-31
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/11035
10.15381/quipu.v22i42.11035
url https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/11035
identifier_str_mv 10.15381/quipu.v22i42.11035
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/11035/9925
dc.rights.none.fl_str_mv Derechos de autor 2014 Janet Cecibel Aldazábal Contreras, Alberto Fernando Napán Vera
https://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2014 Janet Cecibel Aldazábal Contreras, Alberto Fernando Napán Vera
https://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables
publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables
dc.source.none.fl_str_mv Quipukamayoc; Vol. 22 Núm. 42 (2014); 53-59
Quipukamayoc; Vol. 22 No. 42 (2014); 53-59
1609-8196
1560-9103
reponame:Revistas - Universidad Nacional Mayor de San Marcos
instname:Universidad Nacional Mayor de San Marcos
instacron:UNMSM
instname_str Universidad Nacional Mayor de San Marcos
instacron_str UNMSM
institution UNMSM
reponame_str Revistas - Universidad Nacional Mayor de San Marcos
collection Revistas - Universidad Nacional Mayor de San Marcos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 13.78023
DISCRIMINANT ANALYSIS APPLIED TO PREDICTION MODELS IN BANKRUPTCY
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

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