Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms
RESUMEN: This study is motivated by the importance of accurately predicting insolvency before it happens. The paper aims to develop an insolvency prediction model for Colombian firms with one, two and three years of anticipation through financial ratios, keeping sample structures and taking into acc...
- Autores:
-
Correa Mejía, Diego Andrés
Lópera Castaño, Mauricio
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2020
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/15509
- Acceso en línea:
- http://hdl.handle.net/10495/15509
- Palabra clave:
- Quiebra
Bankruptcy
Análisis financiero
Financial analysis
Indicadores económicos
Financial indicators
- Rights
- openAccess
- License
- Atribución 2.5 Colombia (CC BY 2.5 CO)
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| dc.title.spa.fl_str_mv |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| dc.title.alternative.spa.fl_str_mv |
Indicadores financieros como instrumento poderoso para predecir la insolvencia; un estudio usando el algoritmo boosting en empresas colombianas |
| title |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| spellingShingle |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms Quiebra Bankruptcy Análisis financiero Financial analysis Indicadores económicos Financial indicators |
| title_short |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| title_full |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| title_fullStr |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| title_full_unstemmed |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| title_sort |
Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian Firms |
| dc.creator.fl_str_mv |
Correa Mejía, Diego Andrés Lópera Castaño, Mauricio |
| dc.contributor.author.none.fl_str_mv |
Correa Mejía, Diego Andrés Lópera Castaño, Mauricio |
| dc.subject.lemb.none.fl_str_mv |
Quiebra Bankruptcy |
| topic |
Quiebra Bankruptcy Análisis financiero Financial analysis Indicadores económicos Financial indicators |
| dc.subject.ocde.none.fl_str_mv |
Análisis financiero Financial analysis Indicadores económicos Financial indicators |
| description |
RESUMEN: This study is motivated by the importance of accurately predicting insolvency before it happens. The paper aims to develop an insolvency prediction model for Colombian firms with one, two and three years of anticipation through financial ratios, keeping sample structures and taking into account insolvency-related regulation. This research contributes to the literature because unlike many studies, it takes legislation into account, explains the different types of financial ratios, and uses boosting algorithms without biasing the sample. Data from 11,812 Colombian companies covering the period 2012-2016 was used. The results show accuracy above 70% for insolvency prediction with one, two and three years of anticipation. RESUMEN: Esta investigación es motivada por la importancia de tener una buena predicción de la insolvencia con anticipación. El objetivo de este artículo es desarrollar un modelo predictivo para las empresas colombianas con uno, dos y tres años de anticipación usando indicadores financieros, conservando la estructura de la muestra original y teniendo en cuenta la regulación sobre insolvencia. Este artículo contribuye a la literatura ya que, a diferencia de los estudios tradicionales, se tienen en cuenta aspectos como la legislación, se explican los diferentes tipos de indicadores financieros y se utiliza el algoritmo boosting sin sesgar la muestra inicial. Para el desarrollo de este estudio se consideró una muestra de 11.812 empresas colombianas durante el periodo 2012. |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-07-17T17:55:34Z |
| dc.date.available.none.fl_str_mv |
2020-07-17T17:55:34Z |
| dc.date.issued.none.fl_str_mv |
2020 |
| dc.type.spa.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.redcol.spa.fl_str_mv |
https://purl.org/redcol/resource_type/ART |
| dc.type.local.spa.fl_str_mv |
Artículo de investigación |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
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0123-5923 |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10495/15509 |
| dc.identifier.doi.none.fl_str_mv |
10.18046/j.estger.2020.155.3588 |
| dc.identifier.eissn.none.fl_str_mv |
2665-6744 |
| identifier_str_mv |
0123-5923 10.18046/j.estger.2020.155.3588 2665-6744 |
| url |
http://hdl.handle.net/10495/15509 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.rights.*.fl_str_mv |
Atribución 2.5 Colombia (CC BY 2.5 CO) |
| dc.rights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/2.5/co/ |
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http://purl.org/coar/access_right/c_abf2 |
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https://creativecommons.org/licenses/by/4.0/ |
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Atribución 2.5 Colombia (CC BY 2.5 CO) https://creativecommons.org/licenses/by/2.5/co/ http://purl.org/coar/access_right/c_abf2 https://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Icesi, Facultad de Ciencias Administrativas y Económicas |
| dc.publisher.place.spa.fl_str_mv |
Cali, Colombia |
| institution |
Universidad de Antioquia |
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andres.perez@udea.edu.co |
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Correa Mejía, Diego AndrésLópera Castaño, Mauricio2020-07-17T17:55:34Z2020-07-17T17:55:34Z20200123-5923http://hdl.handle.net/10495/1550910.18046/j.estger.2020.155.35882665-6744RESUMEN: This study is motivated by the importance of accurately predicting insolvency before it happens. The paper aims to develop an insolvency prediction model for Colombian firms with one, two and three years of anticipation through financial ratios, keeping sample structures and taking into account insolvency-related regulation. This research contributes to the literature because unlike many studies, it takes legislation into account, explains the different types of financial ratios, and uses boosting algorithms without biasing the sample. Data from 11,812 Colombian companies covering the period 2012-2016 was used. The results show accuracy above 70% for insolvency prediction with one, two and three years of anticipation. RESUMEN: Esta investigación es motivada por la importancia de tener una buena predicción de la insolvencia con anticipación. El objetivo de este artículo es desarrollar un modelo predictivo para las empresas colombianas con uno, dos y tres años de anticipación usando indicadores financieros, conservando la estructura de la muestra original y teniendo en cuenta la regulación sobre insolvencia. Este artículo contribuye a la literatura ya que, a diferencia de los estudios tradicionales, se tienen en cuenta aspectos como la legislación, se explican los diferentes tipos de indicadores financieros y se utiliza el algoritmo boosting sin sesgar la muestra inicial. Para el desarrollo de este estudio se consideró una muestra de 11.812 empresas colombianas durante el periodo 2012.application/pdfengUniversidad Icesi, Facultad de Ciencias Administrativas y EconómicasCali, Colombiainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARTArtículo de investigaciónhttp://purl.org/coar/version/c_970fb48d4fbd8a85Atribución 2.5 Colombia (CC BY 2.5 CO)info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0/Financial Ratios as a Powerful Instrument to Predict Insolvency; a Study Using Boosting Algorithms in Colombian FirmsIndicadores financieros como instrumento poderoso para predecir la insolvencia; un estudio usando el algoritmo boosting en empresas colombianasQuiebraBankruptcyAnálisis financieroFinancial analysisIndicadores económicosFinancial indicatorsEstudios Gerenciales: Journal of Management and Economics for Iberoamerica2020CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823http://bibliotecadigital.udea.edu.co/bitstream/10495/15509/2/license_rdfb88b088d9957e670ce3b3fbe2eedbc13MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/15509/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53ORIGINALCorreaMejiaDiego_2020_FinancialRatiosPowerful.pdfCorreaMejiaDiego_2020_FinancialRatiosPowerful.pdfArtículo de investigaciónapplication/pdf965827http://bibliotecadigital.udea.edu.co/bitstream/10495/15509/1/CorreaMejiaDiego_2020_FinancialRatiosPowerful.pdf608ae26e65c4707be84633b3f9d97efaMD5110495/15509oai:bibliotecadigital.udea.edu.co:10495/155092021-04-30 18:21:31.423Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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 |