Articlediamond2016

Performance Comparison of Multiple Discriminant Analysis and Logit Models in Bankruptcy Prediction

86 citations0/0 files storedEconomics & Sociology

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

Abstract

In this study, the attention is dedicated to the development of bankruptcy prediction model in Slovak Republic.The presented paper focuses on the comparison of overall prediction performance of the two developed models.The first one is estimated via discriminant analysis, while the another is based on a logistic regression.The sample is made up of 236 firms operating in Slovakia, divided into two groups -failed and non-failed firms.The results of the study suggest that the model based on a logit function outperforms the classification accuracy of the discriminant model.The most significant predictors of impeding firms´ failure appear to be Net Income to Total Assets, Current Ratio and Current liabilities to Total Assets.

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 2000Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 1990A neural network model for bankruptcy prediction 1994Bankruptcy prediction using neural networks 1996A survey of business failures with an emphasis on prediction methods and industrial applications 1985ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS

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2017Logit and Probit application for the prediction of bankruptcy in Slovak companies 2018Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries 2017PREDICTIVE POTENTIAL AND RISKS OF SELECTED BANKRUPTCY PREDICTION MODELS IN THE SLOVAK BUSINESS ENVIRONMENT 2018Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis 2020

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