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Titel (übersetzt): 
Predicción de la quiebra empresarial: El modelo GRASP-LOGIT
Erscheinungsjahr: 
2018
Quellenangabe: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 26 [Year:] 2018 [Pages:] 294-314
Verlag: 
Universidad Pablo de Olavide, Sevilla
Zusammenfassung: 
Predicting corporate failure is an important problem in management science. This study tests a new method for predicting corporate failure on a sample of Spanish firms. A GRASP (Greedy Randomized Adaptive Search Procedure) strategy is proposed to use a feature selection algorithm to select a subset of available financial ratios, as a preliminary step in estimating a model of logistic regression for predicting corporate failure. Selecting only a subset of variables (financial ratios) reduces the costs of data acquisition, increases prediction accuracy by excluding irrelevant variables, and provides insight into the nature of the prediction problem allowing a better understanding of the final classification model. The proposed algorithm, that it is named GRASP-LOGIT algorithm, performs better than a simple logistic regression in that it reaches the same level of forecasting ability with fewer accounting ratios, leading to a better interpretation of the model and therefore to a better understanding of the failure process.
Schlagwörter: 
Financial distress
accounting ratios
feature selection
GRASP metaheuristic
logistic regression
JEL: 
C39
C44
G33
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