Analysis of the Economic Sustainability of the Supply Chain Sector by Applying the Altman Z-Score Predictor

This paper fills the gap in the financial perspective of supply chain performance measurement, related to the lack of a bankruptcy probability indicator, and proposes a predictor which is the eighth-model of the Altman Z-Score Logistic Regression. Furthermore, a bankruptcy probability ranking is established for the companies’ supply chains, according to the industry to which they belong. Moreover, the values are set to establish three categories of companies according to predictor. The probability of bankruptcy is analysed and studied for the supply chain of different industries. The building industry is revealed to have the highest probability of bankruptcy.

Bankruptcy Prediction for Innovative Companies

The main purpose of this article is to identify the best neural network model algorithm and relevant set of variables for predicting financial distress/bankruptcy in innovative companies. While previous articles in this area considered neural network analysis for large companies from primary sectors of the economy, we take the novel approach of examining theless-explored area of innovative companies. First, we complete a comprehensive review of the relevant literature in order to define the best configuration of factors which can influence bankruptcy, network architecture and learning methodology. We apply our chosen method to a sample of companies from around the world, from industries which are considered innovative, and identify the dependence of bankruptcy probability on a set of factors which are reflected in the financial data of a company. Our evaluation is based on the financial data of 300 companies – 50 of them are bankrupts, and 250 are ‘healthy’. Our results represent the set of relevant factors for bankruptcy prediction and the appropriate neural network. We have applied a total of 19 factors characterising efficiency, liquidity, profitability, sustainability, and level of innovation. Our proposed analysis is appropriate for all sizes of companies. We provided two models in order to cater for the most confidence in terms of obtained results. The total predictive ability of the model developed in our research is almost 98%, which is extremely efficient, and corresponds to the results of the most modern methods. Both approaches demonstrated almost the same level of influence of factor groups on final bankruptcy probability.

Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies

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.

MODELLING OF INSURANCE COVERAGE CONTINUITY PROVIDING IN MINING INDUSTRY IN CRISIS

BANKRUPTCY PROBABILITY MODELLING OF INSURANCE COMPANIES IN CRISIS Abstract. To develop scientific and methodological foundations, for creating an dynamic mathematical model of insurance company solvency (bankruptcy probability) considering interest rate and inflation ratio. The study used the general scientific and special methods such as: the method of critical analysis, scientific abstraction and generalization of scientific expertise of recent theoretical studies, system-integrated approach, method of dynamic mathematical modeling. Elaboration of dynamic mathematical model of bankruptcy probability modelling considering inflation (as inflation has negative impact on all aspects of insurance business including insurance reserves) and rate of interest. The peculiarities of insurance companies investment activity have been defined. The estimation of insurance premium that ensures abequate insurance fund value formation, i.e. insurance company solvency formation has been performed. Insurance tariff and supplement value correspondent to defined probability of insurance company bankruptcy have been defined. Methodological approaches of insurance companies solvency (bankruptcy probability) modelling were further developed. The dynamic mathematical model of bankruptcy probability considering inflation and rate of interest has been proposed. Theoretical study was developed to the level of specific techniques and suggestions for improvement of the estimation and prognozing of insurance companies solvency and could be used in strategic, current and operational planning. A comprehensive methodology of supplement estimation allows to respond to the changing market situation by changing the values of insurance tariffs. Keywords: insurance organization, dynamic model, probability of bankruptcy, inflation, rate of interest. JEL Сlassification C15, G22, L6, H12 Formulas: 36; fig.: 0; tabl.: 0; bibl.: 12.

Model Assessment of the Financial Stability of Travel Industry Entities with Reference to Sustainable Development

The article is aimed at describing and testing a methodology for assessing the probability of bankruptcy of an enterprise operating in travel industry. In analyzing the activities of a travel industry entity with reference to sustainable development, attention is focused on indicators of financial stability and one of the main financial risks, i.e., the threat of bankruptcy. Modern methods of discriminant analysis used to determine bankruptcy probability, are analyzed as for the adequacy of their use to assess the activities of travel industry entities, and the specificity of their application is described. The available performance indices of a travel agency are analyzed, whose indicators of bankruptcy probability were defined and interpreted as showing that the financial situation at the travel agency in question was satisfactory as for its sustainable development. It is confirmed that of the most widely used methods estimating bankruptcy probability, Matviychuk's model and a modified Altman model are the most proper ones in assessing travel industry entities. Comparison of the results of their application with the entity classification made on the basis of a more commonly used Beaver coefficient shows a high level of consistency among the discriminant models considered. It is noted that taking into account the specifics of the model application and choosing financial indicators are the key to conducting a qualitative analysis and implementing effective anti-crisis policy at an enterprise with reference to its sustainable development. Further analysis of travel industry entities with reference to sustainable development is planned to be conducted using the concept of dynamic equilibrium of the economic system and its effective development

Financial crisis of real sector enterprises: an integral assessment

Successful crisis resolution of the enterprise depends heavily on its timely detection, which is facilitated by the use of forecasting models. This allows understanding the scale of the problems in a timely manner and developing the appropriate measures, applying various financial mechanisms to prevent it, and in case of occurrence, reducing the amount of losses. In this context, it is important to choose the most optimal informational model that would provide the most objective forecasts, considering the financial activity peculiarities of the analyzed enterprise. Given a wide list of models that predict the financial crisis, there is a need to analyze and select the most accurate model for enterprises in the real economy. Ten Ukrainian machine builders are used to assess the bankruptcy probability using the most popular models; a taxonomic analysis was carried out, which allows systematizing a large amount of data and analyzing their impact on enterprise development. An integral index was determined, which allowed predicting the financial performance dynamics. For each enterprise, ten indicators were used characterizing their financial state for the period 2014–2018. It is substantiated that the selected models differ from each other by the set of initial data and the number of coefficients from four to seven. It is also determined that the efficient use of studied models is quite different; so when choosing a model to predict the bankruptcy probability, it is necessary to consider the peculiarities of the enterprise’s production activity, the accuracy in creating the financial statements and many other factors, including the presence of company’s shares in circulation at the stock market. It is worthwhile to use a taxonomic analysis to make a comprehensive comparison of the enterprise financial state and to substantiate the final choice of the bankruptcy forecasting model.

Bankruptcy is an inevitable fate of repeated investments with leverage

Due to the globalization and computerization of financial and economic activities, numerous repetitive leveraged investments have become possible in stock markets and currency exchanges. In reality, repeated leveraged investments up to 100 times/day are possible via online access. With computer-aided programs, this repetition number may easily increase 1000 times/day. The possibility of bankruptcy in repeated leveraged investments has never been considered in actual practices because the probability of bankruptcy in a single investment trial is almost negligible. Here, we show that the extremely numerous repetitions have a considerable chance of bankruptcy overall, even if the probability of bankruptcy for a single investment is extremely close to zero. The exact relationship between the repetitions and the probability of bankruptcy is approximated well by n(0.63) = m, where 10n is the number of repetitions, 10−m is the bankruptcy probability of a single investment, and n(0.63) is the 63% chance of bankruptcy. Thus, extremely rare events can always lead to bankruptcy in continuously repeated investment, even if the possibility of such an event is almost null. We suggest that the avoidance measure of bankruptcy is necessary in numerous repeated investments even if a single trial is almost certain to win.