Bankruptcy-prediction models for Russian enterprises: Specific sector-related characteristics

Fedorova, Elena; Довженко, С Е; Fedorov, Fedor

doi:10.1134/s1075700716030060

Cited by 14 publications

(11 citation statements)

References 7 publications

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“…On the other hand, the worst models cover six to eight indicators. It is worth mentioning that the most effective models are those that are specially developed and adapted for a specific economic sector (Fedorova et al 2016;Barbuta-Misu and Codreanu 2014). In addition, research by Onofrei and Lupu (2014) proved that the application of discriminant analysis model to the Romanian market is more efficient in comparison to the applied logistic regression model.…”

Section: Traditional Statisticalmentioning

confidence: 99%

A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania

et al. 2019

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Different economic environments differ in their characteristics; this prevents the usage of the same bankruptcy prediction models under different conditions. Objectively, the abundance of bankruptcy prediction models gives rise to the idea that these models are not in compliance with the changing business conditions in the market and do not meet the increasing complexity of business tasks. The purpose of this study is to assess the suitability of existing bankruptcy prediction models and the possibilities to increase the effectiveness of their application. In order to analyze theoretical aspects of the application of bankruptcy forecasting models and frame the research methodology, a systemic comparative and logical analysis of the scientific literature and statistical data, graphic data representation, induction, deduction and abstraction are employed. Results of the analysis confirm research hypotheses that bankruptcy prediction models based on macroeconomic variables are effective in identifying the number of corporate bankruptcies in a country and that the application of the model created on the grounds of macroeconomic indicators together with the traditional bankruptcy prediction model can improve the reliability of bankruptcy prediction. However, it was identified that models which are not specially adapted to companies in the construction sector are also suitable for forecasting their bankruptcies.

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Section: Traditional Statisticalmentioning

confidence: 99%

A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania

et al. 2019

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“…It turned out that only 1 out of 13 of these measures was statistically significant and exhibited discriminatory power. In another publication, Fedorova et al (2016) proposed a change of thresholds to obtain the highest efficiencies for domestic and foreign models in the various sectors. Foreign models allowed for achieving higher efficiencies and the best of them was Zmijewski's model.…”

Section: Russiamentioning

confidence: 99%

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Prusak

2018

IJFS

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Abstract:In developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is. The main objective of the article is the review and assessment of the level of advancement of bankruptcy prediction research in countries of the former Eastern Bloc, in comparison to the latest global research trends in this area. For this purpose, the method of analyzing scientific literature was applied. The publications chosen as the basis for the research were mainly based on information from the Google Scholar and ResearchGate databases during the period Q4 2016-Q3 2017. According to the author's knowledge, this is the first such large-scale study involving the countries of the former Eastern Bloc-which includes the following states: Poland, Lithuania, Latvia, Estonia, Ukraine, Hungary, Russia, Slovakia, Czech Republic, Romania, Bulgaria, and Belarus. The results show that the most advanced research in this area is conducted in the Czech Republic, Poland, Slovakia, Estonia, Russia, and Hungary. Belarus Bulgaria and Latvia are on the other end. In the remaining countries, traditional approaches to predicting business insolvency are generally used.

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“…The predictive power of existing models of financial diagnostics is different. Fedorova et al (2016b) argue that the predictive power of bankruptcy models for companies is 66%. The results of probability on Taffler's model are recognized as one of the highest.…”

Section: Electric Power Transmission and Distribution Losses Amount To Approximately 10% Of Energy Generation Capacitymentioning

confidence: 99%

“…We consider these models as extremely negative implications of companies' financial instability. They include internal factors (Altman, 1968) and macroeconomic indicators (Ohlson, 1980;Fedorova et al, 2016b;Bunn and Redwood, 2003;Hol, 2007;Wadhwani, 1986;Kochugueva et al, 2014).…”

Section: Building a Modelmentioning

confidence: 99%

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Assessing the Financial Stability of Electric Power Organizations

Борисова¹,

Kalugina²,

Kosarenko³

et al. 2019

IJEEP

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Nowadays the economic processes in any world economy are carried out at a rapid pace. They have a strong influence on the activities of companies. In this regard, the electric power companies have faced the issue of increasing the efficiency of companies and reducing the degree of dependence on external factors. Moreover, the successful operation of the majority of modern branches of the national economy depends on the efficient and smooth performance of this business. The purpose of the study is to improve the financial stability indicators of electric power companies. The base of the conducted study includes both general scientific and empirical methods: analysis, synthesis, generalization, modeling, observation, description, measurement, and comparison and the case method, which allow broadening the authors' understanding of the financial stability of the business, proposing its main criteria, and studying the aspects of the financial stability of business exemplified by electric power companies. The study carried out by the authors shows that the financial stability of the country is inextricably linked to the financial stability of organizations. Therefore, they need to be evaluated jointly. The relationship between macroeconomic indicators and the financial stability of business is defined by the authors. The concept of financial stability at the macro and micro levels is generalized. The indicators of financial diagnostics of organizations, characterizing their financial stability have been revealed. A model has been developed that allows determining the degree of the financial stability of electric power companies. The proposed model enables the selection of the most stable and steadily functioning electric power companies out of the significant number of ones in conditions of the uncertainty of the external environment. The results obtained by the authors will give an opportunity to identify not only the most stable business in the electric power industry but also, as a consequence, to determine the most attractive business model that should be adapted to other regions to minimize the adverse effects of situations related to uncertainty.

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Bankruptcy-prediction models for Russian enterprises: Specific sector-related characteristics

Abstract: The predictive power is interpreted in this case as follows: (the share of properly identified bankrupt companies + share of properly classified healthy companies)/2.

Cited by 14 publications

References 7 publications

A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania

A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Assessing the Financial Stability of Electric Power Organizations

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