An Integrated Ranking Model of Tehran Stock Exchange Companies Using Bayesian Best-Worst, CoCoSo, and MARCOS Methods (Case Study: Food and Beverage Companies)
نویسندگان
1 PhD Candidate of Financial Engineering, Department of Finance and Banking, Faculty of Accounting and Management, Allameh Tabatabai University, Tehran, Iran.
2 PhD in Organizational Behavior, Faculty of Management, University of Tehran, Iran
3 Assistant Professor, Department of Management, University of Science and Culture, Tehran, Iran
doi
10.30495/ijfma.2023.68893.1895چکیده
The primary goal of this research is to use Multi-Criteria Decision-Making (MCDM) approaches to assess the performance and rank the firms listed on the Tehran Stock Exchange in the food and beverage industry. The calculation of financial ratios is a principal performance appraisal method. Some of these ratios were utilized to rank companies in this study. Nonetheless, the most challenging problem with studying financial ratios is that each financial metric examines a different facet of a company’s financial performance. As a result, managers and investors may be confused by financial ratios. Hence, solutions are required to overcome these constraints. MCDM methods can provide solutions. As a new MCDM method, the Bayesian Best-Worst was utilized to weight options in this study, given its benefits such as enhanced effectiveness of weights resulting from integrating multiple expert opinions and calculating factor ranking reliability. In addition, in light of the characteristics of MCDM approaches, the CoCoSo and MARCOS methods were used to rank 14 firms listed on the Tehran Stock Exchange in the food and beverage industry over three years (2018-2020). Ultimately, the Borda and Copeland methods were built on to integrate the results of the methods.
