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KARAS, M. REŽŇÁKOVÁ, M.
Original Title
Creating a new bankruptcy prediction model: The grey zone problem
Type
conference paper
Language
English
Original Abstract
Bankruptcy prediction models based on the method of linear discriminant analysis (indexes) represent a widely used tool for analyzing corporate failures or evaluating a companys financial health. However, such models are ineffective in alternative economic environments or industries. This is one of the reasons for the necessity of adjusting existing models or creating better new models. There are many papers on creating bankruptcy prediction models, but many of these papers deal with the problem of finding a better set of predictors or finding a better classification algorithm, while limited attention is paid to the problem of setting optimal cut-off scores or grey zone borders. As the grey zone problem can be viewed as a trade-off between a models accuracy and the number of companies that remain unevaluated, it represents a factor influencing model accuracy and effectiveness. In this paper we aim to suggest a criterion that can be used for deriving a grey zone that on one hand maximizes model accuracy, while on the other hand minimizes the number of unevaluated companies.
Keywords
Bankruptcy model, financial ratios, the prediction accuracy of bankruptcy models
Authors
KARAS, M.; REŽŇÁKOVÁ, M.
RIV year
2014
Released
6. 11. 2014
ISBN
978-0-9860419-3-8
Book
Proceedings of The 24th International Business Information Management Association Conference
Pages from
911
Pages to
919
Pages count
9
BibTex
@inproceedings{BUT110421, author="Michal {Karas} and Mária {Režňáková}", title="Creating a new bankruptcy prediction model: The grey zone problem", booktitle="Proceedings of The 24th International Business Information Management Association Conference", year="2014", pages="911--919", isbn="978-0-9860419-3-8" }