scholarly journals International comparison of the relevant variables in the chosen bankruptcy models used in the risk management

2017 ◽  
Vol 8 (1) ◽  
pp. 143 ◽  
Author(s):  
Katarina Zvarikova ◽  
Erika Spuchlakova ◽  
Gabriela Sopkova
Keyword(s):  
Comparative Study ◽  
Prediction Models ◽  
National Level ◽  
Value Added ◽  
Bankruptcy Prediction ◽  
Financial Health ◽  
Prediction Ability ◽  
International Environment ◽  
The World ◽  
Relevant Variables

Research background: It does not matter if the company is operating in the domestic or in the international environment; its failure has serious impact on its environment. Because of this fact it is not surprising that not only owners of the companies, but also another interested groups are focused on the prediction of the company´s financial health. Purpose of the article: The first studies concerned with this issue are dating back to 1930 but from this time a hundreds of bankruptcy prediction models have been constructed all over the world. Some of them are known world-wide and some of them are known only on the national level. Many researchers share their opinion, that it is not appropriate to use foreign models in the domestic conditions non-critically, because they were constructed in the different conditions. One of the main problems are used variables. Methods: We mention three studies which were focused on the used variables in the bankruptcy prediction models. Our comparative study was concerning with 42 models constructed in the seven chosen transit economics with the aim to realize which variables are relevant and which could be reduce from the bankruptcy prediction models. We focused only on the used variables and abstracted from the used methodology, the date of their construction or the model´s power of relevancy. Findings and Value added: The result of our comparative study is the identification of 20 variables, which were used in three or more prediction models, so we assume that these variables have the best prediction ability in the condition of transit economics and their application should be consider in the construction of new models.

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.

scholarly journals Logit and Probit application for the prediction of bankruptcy in Slovak companies

Equilibrium ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. 775-791 ◽  
Author(s):  
Maria Kovacova ◽  
Tomas Kliestik
Keyword(s):  
Logistic Regression ◽  
Prediction Model ◽  
Statistical Methods ◽  
Prediction Models ◽  
Slovak Republic ◽  
Relevant Literature ◽  
Value Added ◽  
Bankruptcy Prediction ◽  
Data Set ◽  
Prediction Ability

Research background: Prediction of bankruptcy is an issue of interest of various researchers and practitioners since the first study dedicated to this topic was published in 1932. Finding the suitable bankruptcy prediction model is the task for economists and analysts from all over the world. forecasting model using. Despite a large number of various models, which have been created by using different methods with the aim to achieve the best results, it is still challenging to predict bankruptcy risk, as corporations have become more global and more complex. Purpose of the article: The aim of the presented study is to construct, via an empirical study of relevant literature and application of suitable chosen mathematical statistical methods, models for bankruptcy prediction of Slovak companies and provide the comparison of overall prediction ability of the two developed models. Methods: The research was conducted on the data set of Slovak corporations covering the period of the year 2015, and two mathematical statistical methods were applied. The methods are logit and probit, which are both symmetric binary choice models, also known as conditional probability models. On the other hand, these methods show some significant differences in process of model formation, as well as in achieved results. Findings & Value added: Given the fact that mostly discriminant analysis and logistic regression are used for the construction of bankruptcy prediction models, we have focused our attention on the development bankruptcy prediction model in the Slovak Republic via logistic regression and probit. The results of the study suggest that the model based on a logit functions slightly outperforms the classification accuracy of probit model. Differences were obtained also in the detection of the most significant predictors of bankruptcy prediction in these types of models constructed in Slovak companies.

scholarly journals Impact of earnings management on bankruptcy prediction

2021 ◽  
Vol 129 ◽  
pp. 03016
Author(s):  
Maria Kovacova ◽  
Martin Lacny ◽  
Jaroslav Gonos
Keyword(s):  
Literature Review ◽  
Earnings Management ◽  
Prediction Models ◽  
Value Added ◽  
Financial Statements ◽  
Bankruptcy Prediction ◽  
Direct Impact ◽  
Prediction Ability ◽  
Positive View ◽  
The Impact

Research background: Managers of the companies intentionally manipulate business earnings to achieve the required status of the company. Earnings management is a legal and widely preferred phenomenon of business finance that financial managers use to maintain and improve the company´s competitiveness. The consequence of these activities is to provide a positive view for the owners, encourage the profitability for the creditor and the investors as well as demonstrate economic strengths to competitors. Consequently, these activities lead to the modification of financial statements of the companies, which have a direct impact on the prediction ability of bankruptcy models. Purpose of the article: The main goal of the paper is to point out the impact of earnings management in the companies on the possibility and ability of bankruptcy prediction. There is a correlation between application of earnings management in companies followed by changes in financial statements of the companies. Therefore, the ability of bankruptcy prediction models to predict possible financial problems of the company is questionable. Methods: The paper presents the connection of earnings management and its impact on bankruptcy prediction based on the bibliometric overview and deep literature review. Findings & Value added: The paper presents results, connections and impact of earnings management on bankruptcy prediction.

scholarly journals Interdisciplinary approaches to the new paradigm of the global financial and monetary architecture after the Covid 19 pandemic crisis in correlation with the social problems in the EU countries

2021 ◽  
Vol 129 ◽  
pp. 01008
Author(s):  
Ghenadie Ciobanu ◽  
Raluca Florentina Cretu ◽  
Mihai Dinu ◽  
Florin Dobre
Keyword(s):  
Global Economy ◽  
Social Systems ◽  
National Level ◽  
Value Added ◽  
Economic Problem ◽  
New Paradigm ◽  
Interdisciplinary Approaches ◽  
The Social ◽  
The World ◽  
The Impact

Research background: How will the world change after the pandemic? What will be the trends of the global economy after the pandemic in the conditions of digital transformations and the impact of other cutting-edge technologies that will change both the global paradigms of the world economy and the global financial and monetary architecture? It is a problem both globally and in each country. Purpose of the article: In this article we aim to examine the processes of transformation of the financial architecture worldwide in the current conditions of financial-monetary globalization, but also of the revolutionary transformations of digitalization and cybersecurity of national, regional, and global financial systems. Research method: We start from the historical approach of the world financial and monetary phenomenon in correlation with the social evolutions. Another method of research is longitudinal: the study of the world financial and monetary phenomenon in time in the context of building the new paradigm of development at the global level with the transition of building paradigms at the national level. In this context, the statistical method and the method of collecting statistical information are also necessary. Findings & Value added: In the conditions when many countries face various serious problems of social, demographic, mass population migration, imbalances in labor markets, declining quality of life, the new international financial-monetary paradigms, but also regional and national ones demand to be correlated by promoting current policies and building economic, financial-monetary and social systems that correspond to solving these socio-economic problem.

scholarly journals Eliciting Weights of Significance of Criteria for a Monitoring Model of Performance of SMEs for Successful Insolvency Administrator’s Intervention

2019 ◽  
Vol 11 (20) ◽  
pp. 5667 ◽  
Author(s):  
Podviezko ◽  
Kurschus ◽  
Lapinskiene
Keyword(s):  
Major Part ◽  
Prediction Models ◽  
Value Added ◽  
Bankruptcy Prediction ◽  
Multiple Criteria ◽  
Satisfactory Level ◽  
Monitoring Model ◽  
Multiple Criteria Evaluation ◽  
Evaluation And Monitoring ◽  
The Eu

Small and medium-sized enterprises (SMEs) are accounted for as a major part of the economy of the EU in terms of part of the population employed, turnover, value-added, etc. Causes of insolvency of SMEs can be different; they are categorized in the paper. A considerable shift from resolving cases of bankruptcy with the sole aim to satisfy creditors’ rights to augmenting and enhancing liquidation and reorganization procedures evolved interest of the authors in creating efficient bankruptcy prediction models and, in particular, methodologies for evaluation and monitoring of the performance of SMEs. In the paper, we reviewed several initiatives and instruments created by the EU for supporting SMEs. The paper laid a foundation for creating a more comprehensive methodology for evaluation of the state of a firm undergoing the process of reorganization. A hierarchy structure of criteria for the evaluation of SMEs was used in the paper; methodologies for eliciting weights of importance of criteria from experts and gauging the level of concordance of opinions of experts were applied. Resulting weights of criteria of performance of an insolvent SME were obtained; the importance of the managerial category of criteria was revealed. Prominent features of hierarchy structures and methodology of using the structure for calculating ultimate weights were described and demonstrated. Gauging concordance of opinions of experts revealed a satisfactory level of concordance of opinions of experts; this allowed to prepare the ultimate weights of criteria for multiple criteria evaluation of SMEs for further research.

scholarly journals Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis

Equilibrium ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. 569-593 ◽  
Author(s):  
Tomas Kliestik ◽  
Jaromir Vrbka ◽  
Zuzana Rowland
Keyword(s):  
Discriminant Analysis ◽  
Prediction Models ◽  
Value Added ◽  
Bankruptcy Prediction ◽  
Net Income ◽  
Multiple Discriminant Analysis ◽  
Financial Situation ◽  
The Future ◽  
A Company ◽  
Visegrad Group

Research background: The problem of bankruptcy prediction models has been a current issue for decades, especially in the era of strong competition in markets and a constantly growing number of crises. If a company wants to prosper and compete successfully in a market environment, it should carry out a regular financial analysis of its activities, evaluate successes and failures, and use the results to make strategic decisions about the future development of the business. Purpose of the article: The main aim of the paper is to develop a model to reveal the un-healthy development of the enterprises in V4 countries, which is done by the multiple discriminant analysis. Methods: To conduct the research, we use the Amadeus database providing necessary financial and statistical data of almost 450,000 enterprises, covering the year 2015 and 2016, operating in the countries of the Visegrad group. Realizing the multiple discriminant analysis, the most significant predictor and the best discriminants of the corporate prosperity are identified, as well as the prediction models for both individual V4 countries and complex Visegrad model. Findings & Value added: The results of the research reveal that the prediction models use the combination of same financial ratios to predict the future financial development of a company. However, the most significant predictors are current assets to current liabilities ratio, net income to total assets ratio, ratio of non-current liabilities and current liabilities to total assets, cash and cash equivalents to total assets ratio and return of equity. All developed models have more than 80 % classification ability, which indicates that models are formed in accordance with the economic and financial situation of the V4 countries. The research results are important for companies themselves, but also for their business partners, suppliers and creditors to eliminate financial and other corporate risks related to the un-healthy or unfavorable financial situation of the company.

scholarly journals Family businesses and predictability of financial strength: a Hungarian study

2020 ◽  
Vol 18 (2) ◽  
pp. 476-489 ◽  
Author(s):  
Judit Sági ◽  
Nick Chandler ◽  
Csaba Lentner
Keyword(s):  
Prediction Models ◽  
Cash Flows ◽  
Bankruptcy Prediction ◽  
Family Businesses ◽  
Added Value ◽  
Test Results ◽  
Financial Health ◽  
Financial Strength ◽  
Management Perspective ◽  
Practical Implications

The aim of this study is to examine how bankruptcy prediction models forecast financial strength for family businesses. Three predictive tests are used to study financial strength for three consecutive years (2016, 2017 and 2018) for a sample of 462,200 active Hungarian companies using the Amadeus database and expert data. Complex statistical model tests for credit assessment (bankruptcy predictions) are performed by size and ownership of the companies. It is found that the revised Altman model is impeded by a superfluous high weighting on net working capital; therefore, IN05 Quick Test predicted better chances for businesses in generating cash flows in a small emerging economy. By re-formulating the Bankruptcy Index of Karas and Režňáková and refining its coefficients, the modified Bankruptcy Index is more robust for predicting the financial health of family businesses on a cash flow basis. The test results of this modified Bankruptcy Index confirm the relative advance of family businesses in creating added value for owners. Practical implications arise from a management perspective: family businesses work better with predictability of survival in accordance with the model; therefore, their ability to adapt to financial constraints caused by crises is also more promising.

scholarly journals Financial Distress and Bankruptcy Prediction in Conditions of Slovak Republic

2021 ◽  
Vol 92 ◽  
pp. 08017
Author(s):  
Filip Rebetak ◽  
Viera Bartosova
Keyword(s):  
Financial Distress ◽  
Prediction Models ◽  
Financial Analysis ◽  
Slovak Republic ◽  
Value Added ◽  
Theoretical Background ◽  
Bankruptcy Prediction ◽  
Important Place ◽  
Non Profit ◽  
Analysis And Synthesis

Research background: Prediction of bankruptcy has an important place in financial analysis of an organization in the globalized economy. Ever since the first publication of a paper on bankruptcy prediction in 1932, the field of bankruptcy prediction was attracting researchers and scholars internationally. Over the years, there have been a great many models conceived in many different countries, such as Altman’s Z score or Ohlson’s model for use for managers and investors to assess the financial position of a company. Globalization in last few decades has made it even more important for all stakeholders involved to know the financial shape of the company and predict the possibility of bankruptcy. Purpose of the article: We aim in this article to examine the financial distress and bankruptcy prediction models used or developed for Slovakia to provide an overview of possibilities adjusted to specific conditions of the Slovak Republic in context of globalization. We will also look at the possibility of use of these prediction models for assessing financial status of non-profit organizations in the Slovak Republic. Methods: We will use analysis and synthesis of current research and theoretical background to compare existing models and their use. Findings & Value added: We hope to contribute with this paper to the theoretical knowledge in this field by summarizing and comparing existing models used.

scholarly journals Bankruptcy Prediction And Its Effect On Stock Prices As Impact Of The COVID-19 Pandemic

2021 ◽  
Vol 25 ◽  
pp. 567-582
Author(s):  
Muhammad Ramadhani Kesuma ◽  
Felisitas Defung ◽  
Anisa Kusumawardani
Keyword(s):  
Prediction Model ◽  
Strong Evidence ◽  
Stock Prices ◽  
Stock Price ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Business Sector ◽  
The World ◽  
Hotel Sector

As COVID-19 pandemic hit the world since early 2020, one business sector in many countries that struggling to survive is tourism and its derivatives, such as restaurants and hotels.  This study aims to examine the accuracy of the Springate and Grover models in predicting bankruptcy, as well as the effect on stock prices of tourism, restaurant, and hotel sector in Indonesia. The results show that all sample tourism, restaurant, and hotel companies are bankrupt under the Springate model, whilst according to Grover's model the findings are varied during the study period. Furthermore, the Grover model is implied to be more accurate than the Springate model. The effect of both prediction models on stock price appears dissimilar. Springate's prediction model suggests a positive and significant effect on stock prices, whereas there is no strong evidence about the effect of Grover’s prediction model.

Sign in / Sign up

Export Citation Format

Share Document