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A two-stage classification technique for bankruptcy prediction · Study

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ArticleA two-stage classification technique for bankruptcy prediction

Philippe du Jardin2016

Article2016

A two-stage classification technique for bankruptcy prediction

Philippe du Jardin

142 citations·0/0 files stored·European Journal of Operational Research

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 200535 years of studies on business failure: an overview of the classic statistical methodologies and their related problems 1985Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results 1996A survey of business failures with an emphasis on prediction methods and industrial applications

Cited by

2018Banking credit worthiness: Evaluating the complex relationships 2019Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting 2022No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure 2017Two-step classification method based on genetic algorithm for bankruptcy forecasting

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Details

Year2016

Typearticle

Published2016-03-11

VenueEuropean Journal of Operational Research

ISSN-L0377-2217

Languageen

Citations142

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.ejor.2016.03.008

openalex_workW2293081571

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2017Probabilistic modeling and visualization for bankruptcy prediction

2020Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

2019Ensemble learning with label proportions for bankruptcy prediction

2020A Race for Long Horizon Bankruptcy Prediction