Risk of Business Bankruptcy

2022 ◽  
pp. 148-177
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Logit Model ◽  
Correlation Matrix ◽  
Heat Supply ◽  
Prediction Models ◽  
Empirical Studies ◽  
Business Owners ◽  
Financial Health ◽  
Suitable Alternative ◽  
Financial Failure ◽  
Dea Method

Recently, the demand of business owners to ensure the sustainability of their businesses has come to the fore. It results in a focus on identifying the risks of businesses' financial failure. Several prediction models can be applied in a given area. Which of these models is most suitable for Slovak companies? The aim of this chapter was to point out the possibility of applying the DEA method in measuring the financial health of companies and predicting the risk of their possible bankruptcy. The research was carried out on a sample of companies operating in the field of heat supply. The indicators were selected using related empirical studies, a univariate Logit model, and a correlation matrix. In this chapter, two main models were applied: the DEA model and the Logit model. The main conclusion of the paper is that the DEA method is a suitable alternative in assessing businesses' financial health.

scholarly journals Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses

2020 ◽  
Vol 13 (9) ◽  
pp. 212 ◽  
Author(s):  
Róbert Štefko ◽  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Data Envelopment Analysis ◽  
Logit Model ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Estimation Accuracy ◽  
Data Envelopment ◽  
Financial Indicators ◽  
Suitable Alternative ◽  
Financial Difficulties ◽  
Dea Method

The paper deals with methods of predicting bankruptcy of a business with the aim of choosing a prediction method which will have exact results. Existing bankruptcy prediction models are a suitable tool for predicting the financial difficulties of businesses. However, such tools are based on strictly defined financial indicators. Therefore, the Data Envelopment Analysis (DEA) method has been applied, as it allows for the free choice of financial indicators. The research sample consisted of 343 businesses active in the heating industry in Slovakia. Analysed businesses have a significant relatively stable position in the given industry. The research was based on several studies which also used the DEA method to predict future financial difficulties and bankruptcies of studied businesses. The estimation accuracy of the Additive DEA model (ADD model) was compared with the Logit model to determine the reliability of the DEA method. Also, an optimal cut-off point for the ADD model and Logit model was determined. The main conclusion is that the DEA method is a suitable alternative for predicting the failure of the analysed sample of businesses. In contrast to the Logit model, its results are independent of any assumptions. The paper identified the key indicators of the future success of businesses in the analysed sample. These results can help businesses to improve their financial health and competitiveness.

scholarly journals Risk of Bankruptcy, Its Determinants and Models

Risks ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 117 ◽  
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Prediction Models ◽  
Research Problem ◽  
Cost Ratio ◽  
Data Envelopment ◽  
Financial Health ◽  
Important Conclusion ◽  
Suitable Alternative ◽  
Dea Method ◽  
The Right ◽  
Altman Model

In this paper, the following research problem was addressed: Is DEA (Data Envelopment Analysis) method a suitable alternative to Altman model in predicting the risk of bankruptcy? Based on the above-mentioned research problem, we formulated the aim of the paper: To apply DEA method for predicting the risk of bankruptcy and to compare its results with the results of Altman model. The research problem and the aim of the paper follow the research of authors aimed at the application of methods which are appropriate for measuring business financial health, performance and competitiveness as well as for predicting the risk of bankruptcy. To address the problem, the following methods were applied: financial ratios, Altman model for private non-manufacturing firms and DEA method. When applying DEA method, we formulated input-oriented DEA CCR model. We found that DEA method is an appropriate alternative to Altman model in predicting the risk of possible business bankruptcy. The important conclusion is that DEA allows us to apply not only outputs but also inputs. Since prediction models do not include these indicators, DEA method appears to be the right choice. We recommend, especially for Slovak companies, to apply cost ratio when calculating risk of bankruptcy.

scholarly journals Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 160
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Data Envelopment Analysis ◽  
Logit Model ◽  
Estimation Accuracy ◽  
Data Envelopment Analysis Model ◽  
Type I ◽  
Data Envelopment ◽  
Financial Health ◽  
Error Type ◽  
Suitable Alternative ◽  
Dea Model

This paper focuses on business financial health evaluation with the use of selected mathematical and statistical methods. The issue of financial health assessment and prediction of business failure is a widely discussed topic across various industries in Slovakia and abroad. The aim of this paper was to formulate a data envelopment analysis (DEA) model and to verify the estimation accuracy of this model in comparison with the logit model. The research was carried out on a sample of companies operating in the field of heat supply in Slovakia. For this sample of businesses, we selected appropriate financial indicators as determinants of bankruptcy. The indicators were selected using related empirical studies, a univariate logit model, and a correlation matrix. In this paper, we applied two main models: the BCC DEA model, processed in DEAFrontier software; and the logit model, processed in Statistica software. We compared the estimation accuracy of the constructed models using error type I and error type II. The main conclusion of the paper is that the DEA method is a suitable alternative in assessing the financial health of businesses from the analyzed sample. In contrast to the logit model, the results of this method are independent of any assumptions.

scholarly journals Selected Methods of Predicting Financial Health of Companies: Neural Networks versus Discriminant Analysis

Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 505
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová ◽  
Igor Petruška
Keyword(s):  
Discriminant Analysis ◽  
Financial Distress ◽  
Empirical Studies ◽  
Confusion Matrix ◽  
Point Of View ◽  
Brier Score ◽  
Financial Health ◽  
Feed Forward Neural Network ◽  
Error Type ◽  
Suitable Alternative

This paper focuses on the financial health prediction of businesses. The issue of predicting the financial health of companies is very important in terms of their sustainability. The aim of this paper is to determine the financial health of the analyzed sample of companies and to distinguish financially healthy companies from companies which are not financially healthy. The analyzed sample, in the field of heat supply in Slovakia, consisted of 444 companies. To fulfil the aim, appropriate financial indicators were used. These indicators were selected using related empirical studies, a univariate logit model and a correlation matrix. In the paper, two main models were applied—multivariate discriminant analysis (MDA) and feed-forward neural network (NN). The classification accuracy of the constructed models was compared using the confusion matrix, error type 1 and error type 2. The performance of the models was compared applying Brier score and Somers’ D. The main conclusion of the paper is that the NN is a suitable alternative in assessing financial health. We confirmed that high indebtedness is a predictor of financial distress. The benefit and originality of the paper is the construction of an early warning model for the Slovak heating industry. From our point of view, the heating industry works in the similar way in other countries, especially in transition economies; therefore, the model is applicable in these countries as well.

scholarly journals The Application of Graphic Methods and the DEA in Predicting the Risk of Bankruptcy

2021 ◽  
Vol 14 (5) ◽  
pp. 220
Author(s):  
Róbert Štefko ◽  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Performance Indicators ◽  
Principal Component ◽  
Key Performance Indicators ◽  
Research Problem ◽  
Financial Health ◽  
Heat Management ◽  
Dea Model ◽  
Financial Failure ◽  
Pca Method ◽  
Dea Method

The paper deals with the issue of analyzing the financial failure of businesses. The aim was to select key performance indicators entering the DEA model. The research was carried out on a sample of 343 Slovak heat management companies. When addressing the research problem, we made use of multidimensional scaling (MDS) and principal component analysis (PCA), which pointed out the areas of financial health of companies that may predict their financial failure. The core of our interest and research was the data envelopment analysis (DEA) method, which represents a more exact approach to the assessment of financial health. The important finding is that the statistical graphical methods—PCA and MDS—are very helpful in identifying outliers and selecting key performance indicators entering the DEA model. The benefit of the paper is the identification of companies that are at risk of bankruptcy using the DEA method. The originality is the selection of key inputs and outputs to the DEA model by the PCA method.

scholarly journals Benchmarking—A Way of Finding Risk Factors in Business Performance

2021 ◽  
Vol 14 (5) ◽  
pp. 221
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová ◽  
Mária Vrábliková
Keyword(s):  
Risk Factors ◽  
Data Envelopment Analysis ◽  
Heat Supply ◽  
Business Performance ◽  
Data Envelopment ◽  
Performance Factors ◽  
Best Value ◽  
Target Values ◽  
Dea Method ◽  
Comparison Of The Results

The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.

scholarly journals Empirics of Korean Shipping Companies’ Default Predictions

Risks ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 159
Author(s):  
Sunghwa Park ◽  
Hyunsok Kim ◽  
Janghan Kwon ◽  
Taeil Kim
Keyword(s):  
Logit Model ◽  
Prediction Models ◽  
Predictive Ability ◽  
Financial Ratios ◽  
Probability Of Default ◽  
Shipping Industry ◽  
Market Participants ◽  
Korean Economy ◽  
Default Prediction ◽  
Financial Characteristics

In this paper, we use a logit model to predict the probability of default for Korean shipping companies. We explore numerous financial ratios to find predictors of a shipping firm’s failure and construct four default prediction models. The results suggest that a model with industry specific indicators outperforms other models in predictive ability. This finding indicates that utilizing information about unique financial characteristics of the shipping industry may enhance the performance of default prediction models. Given the importance of the shipping industry in the Korean economy, this study can benefit both policymakers and market participants.

scholarly journals Family Businesses in Global Economy and Evaluating their Financial Health Using Bankruptcy Models

2021 ◽  
Vol 129 ◽  
pp. 03031
Author(s):  
Maria Truchlikova
Keyword(s):  
Financial Distress ◽  
Global Economy ◽  
Agricultural Sector ◽  
Prediction Models ◽  
Predictive Accuracy ◽  
Value Added ◽  
Business Environment ◽  
Bankruptcy Prediction ◽  
Family Businesses ◽  
Financial Health

Research background: Predicting and assessing financial health should be one of the most important activities for each business especially in context of turbulent business environment and global economy. The financial sustainability of family businesses has a direct and significant influence on the development and growth of the economy because they still represent the backbone of the economy and play an important role in national economies worldwide accounting. Purpose of the article: We used in this article the financial distress and bankruptcy prediction models for assessing financial status of family businesses in agricultural sector. The aim of the paper is to compare models developed by using three different methods to identify a model with the highest predictive accuracy of financial distress and assess financial health. Methods: The data was obtained from Finstat database. For assessing the financial health of selected family businesses bankruptcy models were used: Chrastinova’s CH-Index, Gurcik’s G-Index (defined for Slovak agricultural enterprises) and Altman Z-score. Findings & Value added: This article summarizes existing models and compares results of assessing financial health of family businesses using three different models.

scholarly journals Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities

2020 ◽  
Vol 13 (5) ◽  
pp. 92
Author(s):  
Katarina Valaskova ◽  
Pavol Durana ◽  
Peter Adamko ◽  
Jaroslav Jaros
Keyword(s):  
Prediction Models ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Confusion Matrix ◽  
Predictive Ability ◽  
Early Warning Systems ◽  
Emerging Countries ◽  
Bankruptcy Prediction ◽  
Financial Health ◽  
Prediction Ability

The risk of corporate financial distress negatively affects the operation of the enterprise itself and can change the financial performance of all other partners that come into close or wider contact. To identify these risks, business entities use early warning systems, prediction models, which help identify the level of corporate financial health. Despite the fact that the relevant financial analyses and financial health predictions are crucial to mitigate or eliminate the potential risks of bankruptcy, the modeling of financial health in emerging countries is mostly based on models which were developed in different economic sectors and countries. However, several prediction models have been introduced in emerging countries (also in Slovakia) in the last few years. Thus, the main purpose of the paper is to verify the predictive ability of the bankruptcy models formed in conditions of the Slovak economy in the sector of agriculture. To compare their predictive accuracy the confusion matrix (cross tables) and the receiver operating characteristic curve are used, which allow more detailed analysis than the mere proportion of correct classifications (predictive accuracy). The results indicate that the models developed in the specific economic sector highly outperform the prediction ability of other models either developed in the same country or abroad, usage of which is then questionable considering the issue of prediction accuracy. The research findings confirm that the highest predictive ability of the bankruptcy prediction models is achieved provided that they are used in the same economic conditions and industrial sector in which they were primarily developed.

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