Models for the Assessment of the Entreprise Bankrupty Risk in Crisis Situations (original) (raw)
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ISI 9th International Conference on Artificial Intelligence, Knowledge Engineering and Databases (AIKED'10), University of Cambridge, World Scientific and Engineering Academy and Society Press, 2010
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Credit risk models, particularly those that seek to understand what signals are given by companies on the verge of bankruptcy, are under constant discussion and continually updated. Statistical models, for example, Discriminant Analysis and Logistic Regression, are traditional and easy to understand. However, new nonstatistical techniques have been recently tested in the financial context, such as the case of machine learning mechanisms. In this paper, we developed bankruptcy forecasting models for non-financial companies, using a data set that covers the period from 1980 to 2014. We examined static variables, growth variables and also growth variation variables in order to discriminate two groups: firms that did not go bankrupt and firms that went bankrupt within one (fiscal) year after analysis of their data. To study the discretionary capacity, we applied seven techniques, among statistics and machine learning. In view of the number of models evaluated, the analyses are rich and ...
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Discriminant Methods for Bankruptcy Prediction - Theory and Applications
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Discriminant analysis consists of assigning an individual to two (or more) distinct populations, on the basis of observations of several characters of the individuals and a sample of observations of these characters from the populations. R. A. Fisher suggested a linear function of variables representing different characters, called linear discriminant function, for classifying an individual into one of the two populations. E. I. Altman adapted this approach to identify bankruptcy risk of corporations. Altman’s model of bankruptcy was estimated for various countries, thereby for Polish economy. Some results of estimation and interpretation of Altman’s model for Polish economy are presented in the paper. Methodological problems of discriminant analysis, especially fulfilling the basic assumptions, the analytical form of the discriminant function, the stability of the model and the estimation problems are also discussed.
Statistical modeling for bankruptcy prediction: A brief survey and new examples for e-commence data
Financial ratio based multivariate discriminant analysis (MDA) has been used as a tool for business forecasting for long time. In this article, we study some of the key issues of MDA in context of bankruptcy prediction, including reducing number of nancial ratios used in the model, the selection of optimal accounting review intervals and noise contamination. Experiments are designed for testing ratio sensitivity and the stability of the MDA models and illustrated using both traditional and eCommerce bankruptcy data. To provide some empirical insights for applications of these models, observations from these experiments are summarized and carefully documented.
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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 comparati...
Predicting Bankruptcy Using Financial Indicators
International Journal of Business Marketing and Management (IJBMM), 2022
All companies are the topic to the bankruptcy risks. If we look at the definition, a bankruptcy risk is the business' disability to deal with payable responsibilities. In the recent past, as a consequence of the dynamization of the financial and economic action of different firms, it has become essential to obtain precise information about bankruptcy. The leading objective of this paper is to explore the impact if financial performance indicators on bankruptcy threat for the companies from our dataset. In order to summarize this analysis, I use a multiple regression because it is important to verify if some financial indicators could have an impact on bankruptcy. The software used is IBM SPSS Statistics, Also, I present descriptive statistics that show a general overview for the variables. The variables that are in the center of analysis Return on Assets, Return on Equity. Gross Profit to Sales and Total Asset Turnover.
Bibliometric analysis of the literature on evaluation models of the bankruptcy risk
Strategic Management
Background: To manage an enterprise effectively, it is necessary to analyze and diagnose its financial condition, an activity that can warn management of dangerous business situations. Topics such as assessing financial position, performance, and risk, especially after situations that involve an economic and financial crisis in the company have been widely discussed in scientific literature. Purpose: The purpose of the research is to highlight the main research trends regarding bankruptcy risk assessment models. Study design/methodology/approach: The research strategy is based on two main directions: the first involves the selection of research papers with topics on Conan & Holder and Taffler models published on WoS between 2007 and 2021 and those published on SCOPUS between 2006 and 2021. The second direction aims to select the relevant papers and perform a content analysis of financial-accounting information of Conan & Holder and Taffler models. Findings/conclusions: The results o...
Prediction of Bankruptcy Risk Using Financial Distress Analysis
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Financial distress analysis using X-Score Zmijewski model, Z-Score Altman model, and S-Score model Springate is intended to determine the potential for bankruptcy at PT. Hero Supermarket, Tbk. Secondary data was used in the 2016-2020 financial statements. The results of the calculation of the X-Score method from 2016 - 2019 were in a non-financial distress condition, but in 2020 they were in a distressed situation. This follows the X-Score principle, which focuses on the company's liabilities. We decrease the safe zone to the danger zone from the Z-Score method. In the S-Score process, the company can go bankrupt. The analysis results of the three ways conclude that the company is experiencing financial difficulties. Fast and appropriate handling is needed to fix its condition, and management must improve financial performance. Company management must improve financial conditions, significantly reducing total liabilities every year. The actual existing company liabilities are no...