A Global Model for Bankruptcy Prediction

被引:43
作者
Alaminos, David [1 ]
del Castillo, Agustin [1 ]
Angel Fernandez, Manuel [1 ]
机构
[1] Univ Malaga, Dept Finance & Accounting, Malaga, Spain
关键词
SUPPORT VECTOR MACHINES; FINANCIAL DISTRESS; DISCRIMINANT-ANALYSIS; CORPORATE BANKRUPTCY; EMPIRICAL-EVIDENCE; LISTED COMPANIES; NEURAL-NETWORKS; DEFAULT RISK; LOGIT; RATIOS;
D O I
10.1371/journal.pone.0166693
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.
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页数:18
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