Financial Distress of Companies Listed on the Tehran Stock Exchange using the Dynamic Worst Practice Frontier-based DEA Model

Subject Areas : Financial and Economic Modelling

Hamid Rahimi ¹ , Mehrzad Minouei ² , MohammadReza Fathi ³

1 - Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Faculty of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran

Received: 2021-05-26 Accepted : 2021-09-11 Published : 2022-04-01

Keywords: Improvement Solutions, and Exchange Organization, Securities, Worst-Practice-Frontier DEA, Financial Distress,

Abstract :

One of the main concerns of financial institutions for investing in companies is to evaluate financial performance and, most importantly, the financial distress of organizations applying for investment. Therefore, various approaches and tech-niques are used in this evaluation. Financial decision-making has always been associated with the risk of uncertainty. One way to help investors is to provide forecasting models for the overall corporate prospect. It is noteworthy that in all these approaches, various criteria are used to identify corporate financial distress. In this study, a dynamic worst-practice-frontier DEA model was used to identify financially distressed decision-making units over several time-periods. Another feature of the model presented in this study was to provide some improvement solutions for financially distressed decision-making units. Finally, a new ranking approach was introduced to evaluate companies based on the inefficiency trend over several time-periods. The study's approach provides decision-makers with the ability to evaluate the inefficient DMUs during each time-period according to the relationships between these time-periods. The efficiency slope can also be evaluated over time-periods, and companies can be ranked based on this slope. Finally, it is suggested to use this model to dynamically predict financial distress in various industries, including metals, rubber, automobiles, etc., so that compa-nies are informed of their financial distress promptly and take appropriate measures to prevent bankruptcy.

References:

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