BALANCED BAGGING WITH EXPECTATION MAXIMIZATION IMPUTATION IN BANKRUPTCY PREDICTION – APPLICATION ON ROMANIAN COMPANIES

Abstract

Bankruptcy prediction models are widely used by lending institutions, policy makers or investors. Despite the large volume of international research, limited studies have addressed the particularities of Romanian companies. Balanced Bagging is an Ensemble Method that uses a voting mechanism for a classification task. Expectation Maximization Imputation helps replacing the missing data. In this study we report a promising accuracy performance of 90.03% for the model of Balanced Bagging with Expectation Maximization Imputation on a dataset of more than 20,000 Romanian companies.