An analysis of the effectiveness of bankruptcy prediction models – an industry approach

Abstract Research background: Bankruptcy prediction models are frequently used in research. However, an industry approach is not often carried out. Due to this, this study included trends observable between the number of bankruptcies and its prediction by models. Purpose: The aim of the paper is to verify if changes in the number of actual bankruptcy in individual industries are properly predicted by the models. Also, if analyzed models are providing consistent information according to the risk of bankruptcy between industries. Research methodology: The data were collected from the Orbis database and the Coface reports. The period included in the study is 2014–2019. 5 Polish bankruptcy prediction models were used: these by D. Hadasik, E. Mączyńska and M. Zawadzki, M. Pogodzińska and S. Sojak, D. Wierzba and the Poznan one. Results: The analyzed models do not properly predict changes in the number of bankruptcy in individual industries, however, 3 out of 5 correctly predicted the trend for the entire sample. Analyzed models often provide inconsistent information. Hence, it seems sensible to use more than a few models in any further analyzes. Novelty: In the literature of the subject, there are often carried out analyses focused on the effectiveness of bankruptcy prediction models regarding individual companies. This research is focused on the prediction of changes in the number of companies to be considered as at bankruptcy risk between industries, and also on comparing these models.

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Bankruptcy Prediction Models Based on Value Measures

Journal of Risk and Financial Management ◽

10.3390/jrfm14010006 ◽

2020 ◽

Vol 14 (1) ◽

pp. 6

Author(s):

Andrzej Jaki ◽

Wojciech Ćwięk

Keyword(s):

Discriminant Function ◽

Prediction Models ◽

Statistical Significance ◽

Bankruptcy Prediction ◽

Warning Signs ◽

Discriminant Functions ◽

Corporate Risk Management ◽

Bankruptcy Risk ◽

Corporate Risk ◽

Diagnostic Variables

In the existing studies devoted to predicting bankruptcy, the authors of such models only used book measures. Considering the fact that the evolution of corporate measure efficiency (in addition to book measures) brought into existence and exposed the importance of cash measures, market measures, and measures based on the economic profit concept, it is justified to carry out research into the possibility of using these measures as variables within the discriminant function. The studied dataset was divided into a training set and a testing set based on two variants of the sample division. The assessment of the statistical significance of the built discriminant functions as well as the diagnostic variables was conducted using the STATISTICA package. The research was conducted separately for each variant. In the first step, a total of 30 discriminant models were created. This enabled us to select 20 diagnostic variables that were considered within the two models that were characterised by the highest predictive abilities—one for each variant. The discriminant function that was estimated for the first variant was based on the use of eight diagnostic variables, and 13 diagnostic variables were used in the function that was estimated for the second variant. The conducted analysis has proven that shareholder value measures are a useful tool that can be applied for the needs of corporate risk management in the area of the assessment of a firm’s bankruptcy risk. Using two variants of the division of the research sample into the training and testing sets, it turned out that the division affects the predictive efficiency of the discriminant functions. At the same time, the obtained findings tend to claim that the presence of the value measures from all four of the studied groups in the output set of the diagnostic variables is necessary for possibly building the most efficient tool for the early warning signs of bankruptcy risk.

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Dynamic Bankruptcy Prediction Models for European Enterprises

Journal of Risk and Financial Management ◽

10.3390/jrfm12040185 ◽

2019 ◽

Vol 12 (4) ◽

pp. 185 ◽

Cited By ~ 2

Author(s):

Tomasz Korol

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Prediction Models ◽

Bankruptcy Prediction ◽

Decision Makers ◽

Research Approach ◽

Bankruptcy Risk ◽

Testing Sample ◽

Forecasting Models ◽

Two Samples

This manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and multilayer artificial neural network, and decision trees. Such a research approach will answer the question of whether changes in indicators are relevant predictors of a company’s coming financial crisis because declines or increases in values do not immediately indicate that the company’s economic situation is deteriorating. The research relies on two samples of firms—the learning sample of 50 bankrupt and 50 non-bankrupt enterprises and the testing sample of 250 bankrupt and 250 non-bankrupt firms.

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Bankruptcy prediction models for large agribusiness companies in AP Vojvodina

Ekonomika poljoprivrede ◽

10.5937/ekopolj2103805m ◽

2021 ◽

Vol 68 (3) ◽

pp. 805-822

Author(s):

Dragan Milić ◽

Dragana Tekić ◽

Vladislav Zekić ◽

Tihomir Novaković ◽

Milana Popov ◽

...

Keyword(s):

Financial Stability ◽

Agricultural Sector ◽

Prediction Models ◽

Bankruptcy Prediction ◽

Z Score ◽

Food Sector ◽

Bankruptcy Risk ◽

Quick Test ◽

Score Model

The aim of this paper is to present application of different methods used for predicting bankruptcy of large agricultural and food companies in AP Vojvodina, as well as to determine which model is the most suitable for analyzing the companies from the observed sectors. The following three models were applied in the paper: Altman's Z'-score model, Kralicek DF indicators and Kralicek Quick test. The analysis included five companies from the agricultural sector and five companies from the food sector operating on the territory of AP Vojvodina in the period from 2015 to 2019. The results of the research based on the applied models showed that different conclusions can be made about the financial stability of the observed companies. Altman's Z'-score model provided the most rigorous forecast in terms of the bankruptcy risk, while the results of Kralicek DF indicators and Quick test are relatively similar.

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EVALUATION OF ENTERPRISE SURVIVAL: CASE OF LATVIAN ENTERPRISES

Business Management and Education ◽

10.3846/bme.2018.2482 ◽

2018 ◽

Vol 16 (0) ◽

pp. 13-26

Author(s):

Natalia Scacun ◽

Irina Voronova

Keyword(s):

Prediction Models ◽

Bankruptcy Prediction ◽

Point Of View ◽

Parametric Models ◽

Primary Metal ◽

Financial Ratio ◽

Financial Ratio Analysis ◽

The Subject ◽

Survival Potential ◽

Primary Metal Industry

Authors study the nature of insolvency both from the legal point of view and scientist position as well as updating tendencies of an insolvency of enterprises in recent years. The subject of the study has been selected company’s survival potential that is analyzed with financial ratio analysis using bankruptcy prediction models. Considering research results, authors identify models that are applicable to a particular industry. Authors put primary metal industry (NACE 24) for the study. The aim of the paper is to investigate the survival potential of enterprises by testing existing parametric models of insolvency forecasting and assessing their potential for use in the economic conditions of Latvia. During the investigation has been reviewed the concept of the financially healthy company and its relation with the main success development factors.

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Implication of inside-debt: signalling for bankruptcy probabilities within small firms

Baltic Journal of Management ◽

10.1108/bjm-03-2013-0043 ◽

2014 ◽

Vol 9 (2) ◽

pp. 168-188 ◽

Cited By ~ 3

Author(s):

Raul Seppa

Keyword(s):

Financial Risk ◽

Small Firms ◽

Prediction Models ◽

Bankruptcy Prediction ◽

Equity Capital ◽

Bankruptcy Risk ◽

Content Type ◽

Inside Debt ◽

Privately Held Firms ◽

Retained Earnings

Purpose – Small privately held firms extensively use debt provided by principal owners and households (inside-debt) as an alternative capital source to straight equity capital. The purpose of the research study is to investigate inside-debt-bankruptcy relations. Design/methodology/approach – Inside-debt-bankruptcy relation is tested on three prominent bankruptcy prediction models using correlation and logit regression analysis. Sample consists of 314 Estonian small firms. Financial reports of 2007 are modelled against bankruptcies declared in 2009. Findings – Results imply that users of inside-debt are less profitable; they have weaker liquidity position and less retained earnings. Leverage is not found to be significant determinant between inside-debt users and non-users. Fundamental finding of the study suggests that the use of inside-debt is significantly and positively related to bankruptcy probability. While inside-debt carries no risk elements per se, findings are robust to indicate that the use of inside-debt has significant power to signal for increasing bankruptcy risk and as such, reducing information asymmetry of small firms. Research limitations/implications – This study is limited to single country data. Bankruptcy data fall to the period of economical recession. It is suggested to repeat the study in a normal economical situation and to extend sample size over different countries. Practical implications – Findings contribute to the understanding of firms' financial risk, firm behaviour and capital structure development. In a lending industry, results shall supplement to prudent credit risk assessment techniques and design of bankruptcy models in general. Originality/value – To the author's best knowledge, inside-debt-bankruptcy relation is not studied so far in the existing academic literature.

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An Analysis of the Usefulness of Debt Defaults and Going Concern Opinions in Bankruptcy Risk Assessment

Journal of Accounting Auditing & Finance ◽

10.1177/0148558x9801300311 ◽

1998 ◽

Vol 13 (3) ◽

pp. 351-371 ◽

Cited By ~ 29

Author(s):

Benjamin P. Foster ◽

Terry J. Ward ◽

Jon Woodroof

Keyword(s):

Prediction Models ◽

Bankruptcy Prediction ◽

Loan Default ◽

Bankruptcy Risk ◽

Explanatory Variables ◽

Going Concern ◽

Going Concern Opinion ◽

Loan Defaults ◽

The Impact ◽

Covenant Violations

This study extends the research of Hopwood et al. (1994) and Mutchler et al. (1997) by empirically investigating the relationships between loan defaults, violation of loan covenants, going-concern opinions, and bankruptcy in bankruptcy prediction models. One objective of this study is to empirically test the ability of loan defaults/accommodations and loan covenant violations to assess the risk of bankruptcy. Another objective of this study is to investigate the impact of failing to control for these two distress events on results from tests of the usefulness of going-concern opinions in assessing bankruptcy risk. Results suggest that loan default/accommodation and loan covenant violation are both significant explanatory variables of bankruptcy at the time of the last annual report before the event. While a going-concern opinion variable appears to significantly explain bankruptcy, it is not significant when included in a model with loan default/accommodation and covenant violation variables. Consequently, our results suggest that researchers should include both loan default/accommodation and covenant violation as control variables when using bankruptcy to test the usefulness of going-concern opinions.

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Limitations in the Applicability of Bankruptcy Prediction Models

Economic and social alternatives ◽

10.37075/isa.2021.2.02 ◽

2021 ◽

Vol 27 (2) ◽

pp. 19-31

Keyword(s):

Prediction Models ◽

Bankruptcy Prediction ◽

Bankruptcy Risk ◽

Wide Range ◽

Quality Of Accounting Information ◽

Uniform Definition ◽

Definition Of ◽

Specific Definition ◽

Selection Of

The problems associated with the application of bankruptcy prediction models are of a wide range. A review of the literature shows the lack of a uniform definition of bankruptcy. The existing diversity in the definitions of bankruptcy complicates the comparability of the different studies, hence why it is considered appropriate to take the specific definition of bankruptcy that the bankruptcy prediction models are based on into account when applying them in practice. The selection of companies in the various studies has also been the subject of much criticism. The literature also raises the question of the quality of accounting information. There are also discussions about which indicators should be included in the models. Many studies have demonstrated the benefits of including market information as well as non-financial information in bankruptcy risk analysis. There is also no consensus on the statement that data on the cash flow of companies should be used to increase the predictive power of the models.

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