Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286150 
Title (translated): 
Predicción de la quiebra empresarial: El modelo GRASP-LOGIT
Year of Publication: 
2018
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 26 [Year:] 2018 [Pages:] 294-314
Publisher: 
Universidad Pablo de Olavide, Sevilla
Abstract: 
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.
Subjects: 
Financial distress
accounting ratios
feature selection
GRASP metaheuristic
logistic regression
JEL: 
C39
C44
G33
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

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