عنوان مقاله [English]
Bankruptcy is a challenge that especially in this highly competitive era, many companies are faced with. Therefore the analysis and forecasting of bankruptcy are vital, especially for investors. Accordingly, the present study aims to introduce two techniques which are based on Data Envelopment Analysis (DEA) to analyze and predict bankruptcy of the food companies which are listed on Tehran Stock Exchange.
The study is descriptive- functional andassesses the models of bankruptcy analysis, and 58 Food Companies Listed on the stock exchange have been considered as statistical population.
The study results show that the DEA-Discriminant Analysis model was 92% accurate in predicting the bankrupt companies and 70% accurate in predicting the successful companies while the DEA-Additive model was 70% accurate in predicting the bankrupt companies and 90% accurate in predicting the successful companies, so in total the DEA-Discriminant Analysis model is more accurate than the DEA-Additive model, and it is preferred.