Analyzing the performance of DEA models for bankruptcy prediction in the energy sector: with emphasis on Dynamic DEA approach

Subject Areas : Risk Management

Mohammad Ali Khorami ¹ , Seyed Babak Ebrahimi ² , Majid Mirzaee Ghazani ³

1 - Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 - Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 - Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

Received: 2022-09-05 Accepted : 2023-01-01 Published : 2023-09-01

Keywords: bankruptcy risk, Bankruptcy Prediction Models, Data envelopment analysis, Dynamic Data Envelopment Analysis,

Abstract :

Predicting bankruptcy risk is one of the most critical issues in corporate financial decision-making. Investors always try to predict the bankruptcy of a firm to reduce the risk of losing their assets, so they are looking for ways by which they can predict the risk of bankruptcy. We predict the position of companies active in the oil and gas industry based on their financial health in the 2020 ranking of S&P global up to three years before 2020. This study uses three data envelopment analysis models (CCR, BCC, and DDEA) and the traditional Altman model for forecasting. We have shown that dynamic data envelopment analysis is a powerful tool for predicting bankruptcy risk.

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