In recent decades, predicting company bankruptcies and financial troubles has become a major concern for various stakeholders. Furthermore, because financially sustainable businesses are affected by numerous highly complex factors, both internal and external, the situation is even more complex. This paper applies Altman’s Z-score models; more precisely, the paper applies the initial Z-score model (a model for manufacturing companies), the Z′-score model (for companies operating in emerging markets), and the Z-score bankruptcy probability calculation. Therefore, this paper offers the results of the application of different Z-score models and the calculation of bankruptcy probability on a sample of agricultural companies listed on the Belgrade Stock Exchange in the period 2015–2019. In addition, different Z-score models are used for the same sample so that the difference between their results and application can be determined. In addition, the validity of the data published in the financial statements of the respective companies was confirmed using the Beneish M-score model with five and eight variables. The results obtained by applying Altman’s Z-score model (initial and adapted to emerging markets) indicate that a certain number of companies had impaired financial stability during the observed period, i.e., that they were in danger of bankruptcy. In addition, based on the results obtained using the Beneish M-score model, it was identified that a number of companies showed signals that indicate possible fraudulent financial reporting. Further, it was found that less than half of the observed companies reported on environmental protection in their annual reports, and they did so by providing a modest amount of information. The originality and value of the paper lies in suggesting that policymakers in the Serbian emerging markets should pay more attention to the operations of companies from the observed sector, as well as to their financial and non-financial reporting. Future research should focus on comparisons with agricultural companies from the same sector whose securities are listed on stock exchanges in the region.
The aim of this study is to propose a fuzzy multi-criteria model that will facilitate the assessment of insurance companies' efficiency. This study includes all companies operating within the insurance sector in Serbia in the period from 2007 to 2014 and the data were used from the published financial statements of insurance companies. Five key indicators were identified for the assessment and rating of insurance companies. Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) were used for building the proposed model. In the first stage, priority weights of criteria were defined by using the FAHP, while in the second phase the insurance companies were ranked using the TOPSIS method. JEL CODES c2; c6; G22 ARTICLE HISTORY
Monitoring the financial health of a company to prevent bankruptcy is not only a matter of interest to owners, management and creditors as previously thought, but also a subject of interest to the wider community due to the consequences that bankruptcy may cause. There are numerous models for predicting bankruptcy, but one of the most commonly used is Altman's Z-score model. Over time, the model has been modified so that from its initial form that was intended solely for one enterprise model, today we have a model that can be applied to manufacturing, service, public and private enterprises, as well as to businesses operating in developing markets. The paper uses Altman's Z-score model for companies operating in developing markets to assess the financial health, that is, the possibility of bankruptcy in a sample of 7 hotel companies listed on the Belgrade Stock Exchange.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.