Una revisión sistemática de la literatura en torno a la quiebra empresarial para el período 2012- 2017

Armando L. Támara; Gladis C. Villegas; Javier De Andrés

Una revisión sistemática de la literatura en torno a la quiebra empresarial para el período 2012- 2017

Armando L. Támara, Gladis C. Villegas, Javier De Andrés

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

Resumen

This paper develops a general framework establishing the minimum guidelines required for the study of corporate bankruptcy, framed in five elements such as the definition, sample, cost of error, statistical techniques and variables of prediction models. We analyze 143 articles published in ISI Web of Science and SCOPUS for the period 2012-2017, finding that the most used techniques are neural networks, support vector models and decision trees, while discriminant and logistic models are used as a benchmark.

Título traducido de la contribución	A systematic review of the literature on corporate bankruptcy for the period 2012-2017
Idioma original	Español
Publicación	Espacios
Volumen	40
N.º	4
Estado	Publicada - 1 ene. 2019

Palabras clave

Business bankruptcy
Financial indicators
Indicadores financieros
Modelos de predicción
Prediction models
Quiebra empresarial

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title = "Una revisi{\'o}n sistem{\'a}tica de la literatura en torno a la quiebra empresarial para el per{\'i}odo 2012- 2017",

abstract = "This paper develops a general framework establishing the minimum guidelines required for the study of corporate bankruptcy, framed in five elements such as the definition, sample, cost of error, statistical techniques and variables of prediction models. We analyze 143 articles published in ISI Web of Science and SCOPUS for the period 2012-2017, finding that the most used techniques are neural networks, support vector models and decision trees, while discriminant and logistic models are used as a benchmark.",

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AU - De Andrés, Javier

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N2 - This paper develops a general framework establishing the minimum guidelines required for the study of corporate bankruptcy, framed in five elements such as the definition, sample, cost of error, statistical techniques and variables of prediction models. We analyze 143 articles published in ISI Web of Science and SCOPUS for the period 2012-2017, finding that the most used techniques are neural networks, support vector models and decision trees, while discriminant and logistic models are used as a benchmark.

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KW - Financial indicators

KW - Indicadores financieros

KW - Modelos de predicción

KW - Prediction models

KW - Quiebra empresarial

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Una revisión sistemática de la literatura en torno a la quiebra empresarial para el período 2012- 2017

Resumen

Palabras clave

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Huella

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