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A Global Model for Bankruptcy Prediction

The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the c...

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Detalles Bibliográficos
Autores principales: Alaminos, David, del Castillo, Agustín, Fernández, Manuel Ángel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5120822/
https://www.ncbi.nlm.nih.gov/pubmed/27880810
http://dx.doi.org/10.1371/journal.pone.0166693
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author Alaminos, David
del Castillo, Agustín
Fernández, Manuel Ángel
author_facet Alaminos, David
del Castillo, Agustín
Fernández, Manuel Ángel
author_sort Alaminos, David
collection PubMed
description The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.
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spelling pubmed-51208222016-12-15 A Global Model for Bankruptcy Prediction Alaminos, David del Castillo, Agustín Fernández, Manuel Ángel PLoS One Research Article The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy. Public Library of Science 2016-11-23 /pmc/articles/PMC5120822/ /pubmed/27880810 http://dx.doi.org/10.1371/journal.pone.0166693 Text en © 2016 Alaminos et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Alaminos, David
del Castillo, Agustín
Fernández, Manuel Ángel
A Global Model for Bankruptcy Prediction
title A Global Model for Bankruptcy Prediction
title_full A Global Model for Bankruptcy Prediction
title_fullStr A Global Model for Bankruptcy Prediction
title_full_unstemmed A Global Model for Bankruptcy Prediction
title_short A Global Model for Bankruptcy Prediction
title_sort global model for bankruptcy prediction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5120822/
https://www.ncbi.nlm.nih.gov/pubmed/27880810
http://dx.doi.org/10.1371/journal.pone.0166693
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