Predicting corporate failurethe GRASP-LOGIT Model

  1. Silvia Casado Yusta 1
  2. Laura Nuñez Letamendía 2
  3. Joaquín Antonio Pacheco Bonrostro 1
  1. 1 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

  2. 2 IE Business School, IE University
Revista:
Revista de métodos cuantitativos para la economía y la empresa

ISSN: 1886-516X

Año de publicación: 2018

Volumen: 26

Páginas: 294-314

Tipo: Artículo

Otras publicaciones en: Revista de métodos cuantitativos para la economía y la empresa

Resumen

La predicción de la quiebra empresarial es un problema que goza de una gran relevancia en las ciencias empresariales. En este trabajo se propone un nuevo método para predecir la quiebra empresarial en una muestra de empresas españolas. Concretamente se trata de un algoritmo de selección de variables basado en la estrategia metaheurística GRASP (procedimiento de búsqueda adaptativa aleatoria y voraz) para seleccionar un subconjunto de ratios financieros, como un paso preliminar para estimar un modelo de regresión logística que prediga la quiebra empresarial. La selección de un subconjunto de ratios financieros, de entre todos los disponibles, reduce los costes de adquisición de datos, aumenta la precisión de la predicción al excluir las variables irrelevantes y proporciona información sobre la naturaleza del problema de predicción. Todo lo anterior permite una mejor comprensión del modelo de clasificación final. Nuestro nuevo modelo, al que llamamos modelo GRASP-LOGIT, funciona mejor que una simple regresión logística en el sentido de que alcanza el mismo nivel de capacidad de predicción con menos ratios contables, lo que lleva a una mejor interpretación del modelo y, por lo tanto, a una mejor comprensión del proceso de quiebra empresarial.

Información de financiación

This work has been partially supported by FEDER funds and the Spanish Ministry of Economy and Competitiveness (Projects ECO2013-47129-C4-3-R and ECO2016-76567-C4-2-R), the Regional Government of “Castilla y León”, Spain (Project BU329U14) and the Regional Government of “Castilla y León” and FEDER funds (Project BU062U16); all of whom are gratefully acknowledged.

Financiadores

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