DEVELOPING A MODEL TO PREDICT CORPORATE BANKRUPTCY USING DECISION TREE IN THE REPUBLIC OF SERBIA

Sanja Vlaović Begović, Ljiljana Bonić

DOI Number
https://doi.org/10.22190/FUEO191118010V
First page
127
Last page
139

Abstract


Decision trees made by visualizing the decision-making process solve a problem that requires more successive decisions to be made. They are also used for classification and to solve problems usually addressed by regression analysis. One of the problems of classification that arises is the proper classification of bankrupt companies and non-bankruptcy companies, which  is then used to predict the likelihood of bankruptcy. The paper uses a random forests decision tree to predict bankruptcy of companies in the Republic of Serbia. The research results show the high predictive power of the model with as much as 98% average prediction accuracy, and it is recommended for auditors, investors, financial institutions and other stakeholders to predict bankruptcy of companies in Republic of Serbia.

Keywords

decision trees, bankruptcy, prediction, model

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References


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DOI: https://doi.org/10.22190/FUEO191118010V

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