Corporate bankruptcy prediction in the Republic of Serbia

Stanišić, Nemanja; Mizdraković, Vule; Knežević, Goranka R

doi:10.5937/industrija41-4024

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…The aim was to use predictors that originate from the period of two years, maximum, before the year for which the forecast is made so that the applicability of the models is magnified. The Altman's Z"-score model was chosen as the foundation for building the models because it is a well-known model for assessing bankruptcy risk and it has confirmed applicability in the economic environment of the Republic of Serbia [1,120,121,123]. It is also the only model that has previously been used to investigate the bankruptcy risk in the hotel industry in the Republic of Serbia [30,123], and so the comparability with these studies is ensured.…”

Section: Methodology Of the Researchmentioning

confidence: 99%

Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models

et al. 2022

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In this paper, we assess the impact of the COVID-19 crisis on the bankruptcy risk of a sample of 100 hotel companies and, consequently, on the hotel industry in the Republic of Serbia. The assessment applies to the period, 2019–2026, with the use of the data on the financial indicators for 2015–2020. Five novel structural time-series models, which have the indicators derived from Altman’s EM Z”-score model as predictors, were used, and a new conceptual framework for assessing bankruptcy risk is provided. The framework expands the applicability of credit-risk-scoring models to multiyear predictions, and it takes into account the dynamism of the transitions of the firms among Altman’s risk zones. The predictions that were obtained when the Springate and Zmijewski scores were applied along with the Altman Z”-scores demonstrate the fair applicability of the scores for the models that are introduced here. The results of the models were confirmed by 270 artificial neural networks and they were compared to the results of the classical time-series models. The crisis started to have a negative effect on bankruptcy risk in 2020, and this effect is expected to rise until 2023; currently, in 2022, the highest number of hotel companies may be headed for bankruptcy. Amelioration in the position of the companies cannot be expected before 2024; however, even in 2026, the risk of bankruptcy will remain high when compared to the pre-COVID-19 period and, thus, the surviving companies will become more fragile to any further exogenous changes. These results provide a basis for the adaption of state-supported measures and business policies in order to withstand the crisis and to ensure sustainability.

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Section: Methodology Of the Researchmentioning

confidence: 99%

Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models

et al. 2022

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“…Rajin et al showed that Kralicek's DF model more effectively indicates the financial state of the company than Altman's Z-score model, considering the characteristics of the market in which the model is formed [73]. Because the number of bankrupt companies in the Republic of Serbia has significantly increased, it is particularly important to emphasize the need to apply a model suitable for emerging economies [74].…”

Section: Predicting Bankruptcy Using Altman's Z-score Model and Determining The Possibility Of Fraudulent Financial Reporting Using The Bmentioning

confidence: 99%

Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies

et al. 2021

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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.

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Reassessment of Corporate Bankruptcy Prediction Models Efficiency: Evidence From Serbia/Поновна Процена Прогностичке Моћи Модела За Предвиђање Стечаја У Републици Србији

Mizdraković

Bokić²

2017

TEME

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Having in mind various negative influences that corporate bankruptcy has on the economy of the Republic of Serbia, corporate bankruptcy prediction is of extreme importance. Therefore, the basic motive for writing this paper was an attempt to assess the possibility of forecasting bankruptcy of business entities which operate on the Republic of Serbia's market. We have calculated the already formed M-score, formed based on the data from the financial statements of Serbian business entities. As a comparison models, we have calculated the two most acknowledged Z-score models. The randomly chosen sample consisted of 35 entities in bankruptcy and the same number of non-bankrupt entities. The goal of the research was to reassess the relevance of the tested models for a longer period, as well as their precision in the corporate bankruptcy prediction in an unstable economic environment of the Republic of Serbia. According to the results, the conclusion is that the tested M-score proved its precision in bankruptcy prediction in Serbia, and its use is, therefore, recommended. On the other hand, the Altman’s Z-score models do not have statistical relevance and hence we recommend that their use for bankruptcy prediction in the Republic of Serbia should be with caution.

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Corporate bankruptcy prediction in the Republic of Serbia

Abstract: The aim of this paper is to present corporate default prediction models constructed in the specific market conditions that prevail in the

Cited by 10 publications

References 15 publications

Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models

Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models

Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies

Reassessment of Corporate Bankruptcy Prediction Models Efficiency: Evidence From Serbia/Поновна Процена Прогностичке Моћи Модела За Предвиђање Стечаја У Републици Србији

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