Financial bankruptcy forecasting model with a two-tier approach in data envelopment analysis with semi-positive and negative indicators

For managers, investors and creditors, it is important to be aware of the continuity of the company. To this end, financial researchers are looking for effective methods to evaluate the company's performance and predict the continuation of its activities in the coming years.

In previous research, the standard data envelopment analysis model has been used to predict corporate bankruptcy. The present study aims to provide a model of data envelopment analysis with semi-positive and negative indicators to predict the bankruptcy of companies operating in the Tehran Stock Exchange. The companies listed on the Tehran Stock Exchange constitute the statistical population of the research. To achieve this goal, a sample consisting of 40 non-bankrupt companies and 20 bankrupt companies in the years 1393 to 1397 were selected. The criterion for selecting bankrupt companies is Article 141 of the Commercial Code.

To combine tax ratios that have a more significant correlation with the financial situation of the company, the combined approach of gray relationship analysis and two-level data envelopment analysis has been used.

Originality/Value:

 First, a two-level data envelopment analysis model for semi-positive and negative indices will be developed, then the correct prediction of bankruptcy with its absence will be examined using the results of the proposed model.