Model for measuring the risk of corporate failure: SMEs in Colombia, a case study
The paper shows a mathematical description of the operational and logistic regression technique based on lectures by authors who have profoundly worked its empirical application. The concept of credit risk is defined in a statistical context. A description of economic activities co...
- Autores:
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Universidad Católica de Pereira
- Repositorio:
- Repositorio Institucional - RIBUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.ucp.edu.co:10785/9798
- Acceso en línea:
- https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580
http://hdl.handle.net/10785/9798
- Palabra clave:
- Rights
- openAccess
- License
- Derechos de autor 2019 Entre Ciencia e Ingeniería
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2022-06-01T19:08:34Z2022-06-01T19:08:34Z2019-07-18https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580http://hdl.handle.net/10785/9798The paper shows a mathematical description of the operational and logistic regression technique based on lectures by authors who have profoundly worked its empirical application. The concept of credit risk is defined in a statistical context. A description of economic activities considered in the study. Then, construction was synthesized in 19 SPSS logistic regression model: definition of group training and selection of variables related to business solvency. Finally,results are presented in tables, with the coding of variables, statistical goodness of fit and predictive power to determine the probability that an SME company insolvent fall and create a risk to creditors. It was found that companies reported accumulated losses are eight times more likely to fall insolvent companies with positive retained earnings.El documento muestra una descripción matemática y operativa de la técnica de regresión logística de acuerdo a disertaciones de autores que han trabajadoprofundamente su aplicación empírica. Se define el concepto de riesgo de crédito en un contexto estadístico. Sigue una descripción de las actividades económicas consideradas en el estudio. Luego, se sintetiza la construcción en SPSS 19 del modelo de regresión logística: definición del grupo de entrenamiento y la selección de variables relacionadas con la solvencia empresarial. Finalmente, los resultados se presentan en tablas, con la codificación delas variables, estadísticos de bondad de ajuste y de poder de pronóstico para determinar la probabilidad de que una empresa PYME caiga en estado de insolvencia y genere un riesgo a sus acreedores. Se encontró que las empresas que reportaron pérdidas acumuladas tienen ocho veces más probabilidades decaer en estado de insolvencia que las empresas con utilidades acumuladas positivas.application/pdfspaUniversidad Católica de Pereirahttps://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580/592Derechos de autor 2019 Entre Ciencia e Ingenieríahttps://creativecommons.org/licenses/by-nc/4.0/deed.es_EShttps://creativecommons.org/licenses/by-nc/4.0/deed.es_ESinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Entre ciencia e ingeniería; Vol 8 No 16 (2014); 16-28Entre Ciencia e Ingeniería; Vol. 8 Núm. 16 (2014); 16-28Entre ciencia e ingeniería; v. 8 n. 16 (2014); 16-282539-41691909-8367Model for measuring the risk of corporate failure: SMEs in Colombia, a case studyModelo para la medición del riesgo de insolvencia empresarial: PYME de Colombia, un caso de estudioArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionCruz Trejos, Eduardo ArturoEspinosa Peña, JaimeAristizábal Hernández, SergioPublication10785/9798oai:repositorio.ucp.edu.co:10785/97982025-01-27 19:00:24.979https://creativecommons.org/licenses/by-nc/4.0/deed.es_ESDerechos de autor 2019 Entre Ciencia e Ingenieríametadata.onlyhttps://repositorio.ucp.edu.coRepositorio Institucional de la Universidad Católica de Pereira - RIBUCbdigital@metabiblioteca.com |
| dc.title.eng.fl_str_mv |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| dc.title.spa.fl_str_mv |
Modelo para la medición del riesgo de insolvencia empresarial: PYME de Colombia, un caso de estudio |
| title |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| spellingShingle |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| title_short |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| title_full |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| title_fullStr |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| title_full_unstemmed |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| title_sort |
Model for measuring the risk of corporate failure: SMEs in Colombia, a case study |
| description |
The paper shows a mathematical description of the operational and logistic regression technique based on lectures by authors who have profoundly worked its empirical application. The concept of credit risk is defined in a statistical context. A description of economic activities considered in the study. Then, construction was synthesized in 19 SPSS logistic regression model: definition of group training and selection of variables related to business solvency. Finally,results are presented in tables, with the coding of variables, statistical goodness of fit and predictive power to determine the probability that an SME company insolvent fall and create a risk to creditors. It was found that companies reported accumulated losses are eight times more likely to fall insolvent companies with positive retained earnings. |
| publishDate |
2019 |
| dc.date.issued.none.fl_str_mv |
2019-07-18 |
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2022-06-01T19:08:34Z |
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2022-06-01T19:08:34Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580 |
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http://hdl.handle.net/10785/9798 |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580 http://hdl.handle.net/10785/9798 |
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spa |
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spa |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/580/592 |
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Derechos de autor 2019 Entre Ciencia e Ingeniería https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES |
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https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES |
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info:eu-repo/semantics/openAccess |
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Derechos de autor 2019 Entre Ciencia e Ingeniería https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
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Universidad Católica de Pereira |
| dc.source.eng.fl_str_mv |
Entre ciencia e ingeniería; Vol 8 No 16 (2014); 16-28 |
| dc.source.spa.fl_str_mv |
Entre Ciencia e Ingeniería; Vol. 8 Núm. 16 (2014); 16-28 |
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Entre ciencia e ingeniería; v. 8 n. 16 (2014); 16-28 |
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2539-4169 1909-8367 |
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Universidad Católica de Pereira |
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Repositorio Institucional de la Universidad Católica de Pereira - RIBUC |
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bdigital@metabiblioteca.com |
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