Search results

1

APPLICATION OF MULTIVARIATE DISCRIMINANT ANALYSIS FOR PREDICTION OF BANKRUPTCY OF SELECTED CONSTRUCTION AND DEVELOPMENT COMPANIES

100%

Zielińska-Sitkiewicz M.

Metody Ilościowe w Badaniach Ekonomicznych

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2014

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vol. 15

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issue 2

261-272

EN

Functioning of the company in the conditions of the free market competition depends on its flexible reactions to changes and the response speed to perturbations in the unstable economy. Entities, which are not able to keep up with the current changes, enter the path of crisis in the company, which last stage may be the bankruptcy. The paper presents an attempt to use and evaluate five Polish models of the multivariate discriminant analysis in forecasting the threat of bankruptcy. The analysis was conducted for the years 2008 – 2013. For the study there were selected 10 construction and real estate development companies, listed on the main market of the Warsaw Stock Exchange, which profit and loss account is made in the calculation model and for which in the years 2012-2014 there were initiated the bankruptcy proceedings.

2

APPLICATION OF MULTIVARIATE DISCRIMINANT ANALYSIS FOR ASSESSMENT OF CONDITION OF CONSTRUCTION COMPANIES

100%

Zielińska-Sitkiewicz M.

Metody Ilościowe w Badaniach Ekonomicznych

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2013

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vol. 14

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issue 2

298-308

EN

The construction is important in a market economy. From the development of the construction industry depends on large extent how the economy will function. Hence, the need for continuous monitoring of both –the market and the use of methods- that will objectively evaluate the quality of the construction companies. The paper contains consideration about usage discriminant analysis in financial audit of construction companies. 30 companies from construction sector, which are listed on the Warsaw Stock Exchange, were selected for study. The analysis encompassed financial data from balance sheets and from profit and loss account in the period from January 1, 2005 to December 31, 2012.

3

THE APPLICATION OF DISCRIMINANT ANALYSIS IN FORECASTING OF INVESTORS' REACTION TO MACROECONOMIC NEWS ANNOUNCEMENTS

100%

Wójtowicz T.

Metody Ilościowe w Badaniach Ekonomicznych

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2014

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vol. 15

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issue 2

252-260

EN

Macroeconomic news announcements, particularly concerning the U.S. economy, have a significant impact on stock markets. Recent studies show that stock prices react significantly as soon as macroeconomic news is announced. However, the strength of the reaction and its duration depends on the market and on the news announced. In this paper, we study the applicability of discriminant analysis in the prediction of direction of changes of the main indices of stock exchanges in Warsaw and Vienna after release of the Employment Report by the U.S. Bureau of Labor Statistics.

4

DEFAULT PREDICTION FOR SME USING DISCRIMINANT AND SURVIVAL MODELS, EVIDENCE FROM POLISH MARKET

100%

Ptak-Chmielewska A., Matuszyk A.

Metody Ilościowe w Badaniach Ekonomicznych

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2014

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vol. 15

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issue 2

369-381

EN

The aim of this paper was to compare the new technique (survival analysis) used in the credit risk models with the traditional one (discriminant analysis), analyse the strengths and weaknesses of both methods and their usage in practice. This study attempts to use macroeconomic data to build models and examine its impact to the prediction. For this purpose, a number of models was built on the basis of the sample of 1547 enterprises including 494 defaults. The time range covered by sample was 2002-2012.

5

The Relevance of Trend Variables for the Prediction of Corporate Crises and Insolvencies

100%

Situm M.

Zagreb International Review of Economics and Business

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2015

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vol. 18

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issue 1

17-49

EN

This study investigated the potential of a specific trend, defined as the relative change of accounting ratios for two consecutive years, to improve the classification accuracy and model performance of insolvency prediction models based on multivariate linear discriminant analysis. The results show that the respective trend can include information from both consecutive years, but this informational content could not be exploited to improve early detection of corporate crises and insolvencies.

6

Gant Development S.A. – the effectiveness of bankruptcy prediction models in case of sudden bankruptcy. Case study

100%

Dzyuma-Zaremba U.

Finansowy Kwartalnik Internetowy e-Finanse

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2015

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vol. 11

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issue 3

45-57

EN

Company bankruptcies are an inseparable element of market economy. We may observe the tendency to view bankruptcy as a problem of weak and usually small entities facing problems when trying to meet the challenge posed by strong competition. Big companies, however, also fall, and their bankruptcy cannot be predicted by even the most experienced analysts. The aim of the article is to examine the effectiveness of the bankruptcy prediction models in case of sudden bankruptcies,on the example of Gant Development S.A. The author attempts to classify the real estate developer’s bankruptcy as “staged” bankruptcy by performing an analysis of company activities in the period of 2010-2013. The study was conducted using Polish models of linear discriminant analysis, widely popular in the Polish literature as well as the models which reflect the branch specificity of the examined entity.

7

An Attempt of Delimitation of Polish Metropolitan Areas by Discriminant Analysis

100%

Zaród J.

Barometr Regionalny. Analizy i prognozy

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2016

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issue 4(46)

39-47

EN

The purpose of this article is a division of Poland into areas with different economic and social conditions and the identification of the areas which may aspire to the name of metropolis. Initial division of Polish territorial units was made on the basis of statistical data on the labor market, wages, public utilities, education, health care, environment, culture, industry and construction. These data were subjected to standardization and were verified as to whether represent a normal distribution. Then the discriminatory power of the variables were examined and parameters of the linear discriminant function were estimated. The highest average value of the discriminant function indicates the area most developed in terms of the examined features. Territorial units that belong to this complex are metropolises or aspire to being them. For each area, the classification functions were estimated and on their basis the final division was made. The allocation to the sub-region was mainly determined by variables such as density of population, unemployment rate, average flat surface and the number of entrepreneurs. In the first group are territorial units that belong already to the metropolitan areas. Subsequent numbers indicate areas with increasingly less economic and social development.

PL

Celem tej pracy jest podział Polski na obszary o różnych warunkach rozwoju gospodarczego i społecznego oraz wyłonienie regionów pretendujących do miana metropolii. Do wyodrębnienia polskich obszarów metropolitalnych wykorzystano dane dotyczące rynku pracy, wynagrodzeń, gospodarki komunalnej, edukacji, ochrony zdrowia i środowiska, kultury, przemysłu i budownictwa. Dane poddano standaryzacji i sprawdzono czy reprezentują one rozkład normalny. Następnie zbadano moc dyskryminacyjną zmiennych i oszacowano parametry liniowych funkcji dyskryminacyjnych. Najwyższa przeciętna wartość funkcji dyskryminacyjnej wskazuje obszar najlepiej rozwinięty pod względem badanych cech. Jednostki terytorialne należące do tego kompleksu są metropoliami lub do nich pretendują. O przydziale podregionów do danego obszaru zadecydowały głównie takie zmienne jak: gęstość zaludnienia, stopa bezrobocia, przeciętna powierzchnia mieszkania oraz liczba podmiotów gospodarczych. W I obszarze znalazły się jednostki terytorialne należące już do obszarów metropolitalnych. Kolejne numery obszarów oznaczają kompleksy o coraz niższym rozwoju gospodarczym i społecznym.

8

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

100%

Svabova L., Kramarova K., Chutka J., Strakova L.

Oeconomia Copernicana

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2020

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vol. 11

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issue 3

485-508

EN

Research background: Misleading financial reporting has a negative impact on all stakeholders since financial records are the primary source of information on financial stability, economic activity, and financial health of any company. The handling of them is primarily the responsibility of managers or owners and reasons for doing so may differ. Their common denominator is the artificial creation of information asymmetry to get different types of benefits. It is, therefore, logical that the issue of detecting opportunistic earnings management comes to the fore. Purpose of the article: The purpose of the study is to create a discriminant model of the detection of earnings manipulators in the conditions of the Slovak economy. Methods: We used the discriminant analysis to create a model to identify fraudulent companies, based on the real data on companies that were convicted from misleading financial reporting in connection with tax fraud in the years 2009-2018. The model is inspired by the Beneish model, which is one of the most applied fraud detection methods at all. Findings & Value added: In order to achieve more accurate detection results, we extended the original model by taking into account the values of indicators from three consecutive years, i.e. by taking into account the development of the potential tendency of companies to be involved in opportunistic earnings management. Our model correctly identified 86.4% of fraudulent companies and overall reaches 84.1% classification ability. Both models were applied on empirical data on 1,900 Slovak companies from the years 2016-2018, while their overlap was 32.7% for fraudulent companies and 38.4% for non-fraud companies. This is a very useful result, as the application of both models rein-forces the results obtained and the identical classification of the company into fraudulent indicates that the manipulation of earnings occurs with a high probability.

9

Macroeconomic factors of economic growth in the European Union in 2000-2016: A multidimensional analysis

100%

Batóg J., Batóg B.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2019

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issue vol. 23 no. 3

1-14

EN

The creation of an effective growth policy requires the identification of its key determinants. The study used one of the methods of multidimensional analysis – discriminant analysis. It is widely used on a microeconomic scale, especially in the area of forecasting bankruptcy of enterprises, but in the area of economic growth, it has not been used in practice so far. In addition to the main objective of identifying the most important economic growth factors of the European Union countries in 2000- 2016, the impact of the crisis and accession to the EU was examined. The statistical data sources were the databases of Eurostat and the Conference Board (Total Economy Database). The results obtained allowed us to conclude that the rate of Gross Domestic Product growth in the EU countries was determined by consumption, investment, export and labour productivity, and in periods of economic slowdown also public debt. The enlargement of the EU resulted in an increase in the importance of export.

10

Modelling the determinants of winning in public tendering

100%

MALARA M., MAZURKIEWICZ M.

Operations Research and Decisions

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2012

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vol. 22

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issue 1

51-62

EN

The purpose of this article is to identify the factors influencing the probability of winning in public procurement procedures and to assess the strength of their impact from the perspective of both: the bidder and procurer. The research was conducted with the use of series of quantitative methods: binary logistic regression, discriminant analysis and cluster analysis. It was based on a sample consisting of public tenders, in which the examined company performed the role of a bidder. Thus, the research process was aimed at both identifying the factors of success and estimating the probability of achieving it, where it was possible to obtain probabilities. The main idea of this research is to answer questions about the utility of various methods of quantitative analysis in the case of analyzing determinants of success. Results of the research are presented in the following sequence of sections: characteristics of the examined material, the process of modelling the probability of winning, evaluation of the quality of the results obtained.

11

Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods

100%

Ptak-Chmielewska A.

Statistics in Transition new series

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2021

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vol. 22

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issue 1

179-195

EN

The impact the last financial crisis had on the small- and medium-sized enterprises (SMEs) sector varied across countries, affecting them on different levels and to a different extent. The economic situation in Poland during and after the financial crisis was quite stable compared to other EU member states. SMEs represent one of the most important segments of the economy of every country. Therefore, it is crucial to develop a prediction model which easily adapts to the characteristics of SMEs. Since the Altman Z-Score model was devised, numerous studies on bankruptcy prediction have been written. Most of them involve the application of traditional methods, including linear discriminant analysis (LDA), logistic regression and probit analysis. However, most recent studies in the area of bankruptcy prediction focus on more advanced methods, such as case-based reasoning, genetic algorithms and neural networks. In this paper, the effectiveness of LDA and SVM predictions were compared. A sample of SMEs was used in the empirical analysis, financial ratios were utilised and non-financial factors were taken account of. The hypothesis assuming that multidimensional discrimination was more effective was verified on the basis of the obtained results.

12

Credibility of Discriminatory Models on the Example of Enterprises from the Lubelskie and Podkarpackie Voivodeships

89%

Pitera R., Chmiel J., Kozioł K.

Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia

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2020

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vol. 54

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issue 3

EN

Theoretical background: The results of the conducted research allowed the classification of early-warning models according to the accuracy of the forecasts received for the last year of the study. Purpose of the article: The aim of the article was verification and prognostic assessment of discriminative models popular among researchers, answer to the question whether the model properly reflects the financial situation of the company. Research methods: The basis of all the methods used in this article was the analysis of existing data and methods of discriminant analysis. Main findings: The selected models properly reflected the financial situation of the 84 enterprises surveyed.

PL

Theoretical background: The results of the conducted research allowed the classification of early-warning models according to the accuracy of the forecasts received for the last year of the study.Purpose of the article: The aim of the article was verification and prognostic assessment of discriminative models popular among researchers, answer to the question whether the model properly reflects the financial situation of the company.Research methods: The basis of all the methods used in this article was the analysis of existing data and methods of discriminant analysis.Main findings: The selected models properly reflected the financial situation of the 84 enterprises surveyed.

13

ANALIZA PORÓWNAWCZA MODELOWANIA LOGITOWEGO I LINIOWEJ FUNKCJI DYSKRYMINACYJNEJ W OCENIE RYZYKA UPADŁOŚCI SPÓŁEK GIEŁDOWYCH

88%

Wojnar J.

Metody Ilościowe w Badaniach Ekonomicznych

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2015

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vol. 16

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issue 4

201-210

PL

W pracy dokonano porównania efektów modelowania logitowego i liniowej funkcji dyskryminacyjnej w ocenie zagrożenia finansowego spółek giełdowych. Badano wpływ różnych wskaźników analizy finansowej na zdolność prognostyczną modeli. Poszukiwano wskaźników, które w najlepszy sposób ostrzegają o zagrożeniu upadłością. Dokonano weryfikacji empirycznej przydatności oszacowanych modeli dla przewidywania upadłości spółek.

EN

In the paper the effects of logit model and discriminant function in the hazard assessment of the companies listed were compared. The effect of different indicators of financial analysis for the predictive ability of the models was studied. The aim was to find indicators which warn about the threat of bankruptcy in the best way.

14

Repair and Renovation Reserve as a Tool of Commonhold Repair and Renovation Policies in Residential Properties Co-owned by Local Councils in Poland

88%

Zapotoczna M., Cymerman J.

Barometr Regionalny. Analizy i prognozy

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2014

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issue 3(37)

59-66

EN

The article discusses the repair and renovation funds as a tool of commonhold repair and renovation policies in residential properties co-owned by Polish local councils (commons). The authors made an attempt to discriminate features of 202 commonholds and form their homogenous groups in order to prove that there was a correlation between the commune’s share in a divided co-property and the commonholds’ repair and renovation policies. The discrimination was based on selected variables and conducted by means of six methods of discriminant analysis. The study covered commonholds co-owned by the commune of Olsztyn which were managed by a community partnership from 2007 to 2011.

PL

Artykuł poświęcono instytucji funduszu remontowego jako narzędzia polityki remontowej wspólnot mieszkaniowych w zasobach z udziałem gminy. Podjęto próbę dyskryminacji 202 wspólnot w grupy jednorodne, w celu wykazania wpływu wysokości udziału gminy w nieruchomości wspólnej na politykę remontową wspólnot mieszkaniowych. Dyskryminacji dokonano na podstawie przyjętych do badania zmiennych za pomocą sześciu metod analizy dyskryminacyjnej. Badaniami objęto wspólnoty mieszkaniowe z udziałem gminy Olsztyn, zarządzane przez komunalną spółkę prawa handlowego w latach 2007–2011.

15

Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis

88%

Kliestik T., Vrbka J., Rowland Z.

Equilibrium. Quarterly Journal of Economics and Economic Policy

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2018

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vol. 13

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issue 3

569-593

EN

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.

16

The Capacity to Forecast Enterprise Insolvency on the Polish Market Using the Precursory Altman Z-Score Model (1968)

88%

Antonowicz P., Antonowicz A.

Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia

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2022

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vol. 56

|

issue 5

7-26

EN

Theoretical background: Many years have passed since the publication of the first multidimensional model (Z-score) of early bankruptcy warning by E.I. Altman in 1968. New models have since emerged in different countries. In this research stream, the share of econometric modelling based on the assumptions of discriminant analysis, i.e. MDA - Multiple Discriminant Analysis - one of the multidimensional classiifcation methods categorised as empirical-induction methods, plays a particularly important role. Purpose of the article: The article assesses the capacity of the Altman Z-Score to forecast (1 year ahead) insolvency of enterprises on the Polish market.

17

General bankruptcy prediction models for the Visegrád Group. The stability over time

88%

TOMCZAK S. K.

Operations Research and Decisions

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2023

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vol. 33

|

issue 4

171-187

EN

Managers of enterprises must constantly face the continual changes on the market and fight for survival in a world of high competition. Therefore, it is important to systematically monitor the company’s financial condition. This will help to identify problems and give specific time to take corrective action. Bankruptcy prediction models are usually constructed for local goals. The purpose of the article is to build not only regional but also general discriminant and logit models for the SMEs operating in the construction industry in Visegrád Group countries. A total of 32 unique models were built and verified along with the Altman model for emerging markets. The paper also contributes to the literature by assessing the stability of the constructed models over time, which the models’ authors do not usually measure. The results showed that regional models are characterized by higher accuracy than general ones. However, general models can be adapted to the analyzed Visegrád Group with an accuracy of approximately 90%. The G1 LR model can be considered the best model, as it has relatively high accuracy and over-time stability.

18

On the binary classification problem in discriminant analysis using linear programming methods

88%

OLUSOLA M. O., ONYEAGU S. I.

Operations Research and Decisions

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2020

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vol. 30

|

issue 1

119-130

EN

This paper is centred on a binary classification problem in which it is desired to assign a new object with multivariate features to one of two distinct populations as based on historical sets of samples from two populations. A linear discriminant analysis framework has been proposed, called the minimised sum of deviations by proportion (MSDP) to model the binary classification problem. In the MSDP formulation, the sum of the proportion of exterior deviations is minimised subject to the group separation constraints, the normalisation constraint, the upper bound constraints on proportions of exterior deviations and the sign unrestriction vis-à-vis the non-negativity constraints. The two-phase method in linear programming is adopted as a solution technique to generate the discriminant function. The decision rule on group-membership prediction is constructed using the apparent error rate. The performance of the MSDP has been compared with some existing linear discriminant models using a previously published dataset on road casualties. The MSDP model was more promising and well suited for the imbalanced dataset on road casualties.

19

Analiza dyskryminacji w identyfikacji dobrobytu ekonomicznego gospodarstw domowych w województwie podkarpackim

75%

Wojnar J., Kasprzyk B.

Metody Ilościowe w Badaniach Ekonomicznych

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2011

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vol. 12

|

issue 2

409-417

PL

W pracy na podstawie danych ankietowych dotyczących próby losowej gospodarstw domowych (w woj. podkarpackim) omówiono przykład zastosowania liniowej funkcji dyskryminacyjnej do modelowania ubóstwa ekonomicznego gospodarstw domowych. Oszacowany istotny statystycznie model dyskryminacyjny pozwala identyfikować gospodarstwa domowe do kategorii ubogich/nieubogich w oparciu o zmienne charakteryzujące uwarunkowania danego gospodarstwa domowego, mające najczęściej charakter jakościowy, głównie demograficzno-społeczny.

EN

The paper discusses an example of applying a linear discriminant function to model the economic poverty of households, on the basis of a survey conducted on a random sample of households in Podkarpackie province. The statistically relevant discriminatory model allows for the identification of poor / not poor categories based on mostly qualitative, demographic and social variables characterizing the households.

20

BUSINESS FAILURE PREDICTION MODELS BASED ON EXPERT KNOWLEDGE

75%

Situm M.

Czech Journal of Social Sciences, Business and Economics

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2013

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vol. Volume 2

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issue 4

28-46

EN

This paper presents two business failure prediction models developed with multivariate linear discriminant analysis and multivariate logistic regression. The financial ratios as predictors for the models were selected based on results from previous empirical research. It was assumed that companies can be categorized into three classes – healthy (group 1), crisis-resistant (group 2) and insolvency endangered (group 3) – which are describing different economic conditions. Data for model building were obtained by a survey of 35 professionals from management consulting and banking industry. The results show consistency with findings of prior research. High values for equity-ratio, EBIT/total assets, operating cashflow/financial liabilities and percentage sales development are positively related to financial health. Within model building several problems occurred, which influenced classification accuracy. Non-normality of data had an impact on discriminant analysis, but also on logistic regression. Successful preliminary analyses of suitable predictors are not a guarantee that model fit including statistically significant variables will provide a superior prediction model. This indicates that model building is heavily dependent on the quality of metrics used. Logistic regression was less sensitive to outliers in terms of prediction sign within classification formula. It was also shown that crisis indicators used in practice are similar to those proposed by empirical research and literature.

Refine search results

APPLICATION OF MULTIVARIATE DISCRIMINANT ANALYSIS FOR PREDICTION OF BANKRUPTCY OF SELECTED CONSTRUCTION AND DEVELOPMENT COMPANIES

APPLICATION OF MULTIVARIATE DISCRIMINANT ANALYSIS FOR ASSESSMENT OF CONDITION OF CONSTRUCTION COMPANIES

THE APPLICATION OF DISCRIMINANT ANALYSIS IN FORECASTING OF INVESTORS' REACTION TO MACROECONOMIC NEWS ANNOUNCEMENTS

DEFAULT PREDICTION FOR SME USING DISCRIMINANT AND SURVIVAL MODELS, EVIDENCE FROM POLISH MARKET

The Relevance of Trend Variables for the Prediction of Corporate Crises and Insolvencies

Gant Development S.A. – the effectiveness of bankruptcy prediction models in case of sudden bankruptcy. Case study

An Attempt of Delimitation of Polish Metropolitan Areas by Discriminant Analysis

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

Macroeconomic factors of economic growth in the European Union in 2000-2016: A multidimensional analysis

Modelling the determinants of winning in public tendering

Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods

Credibility of Discriminatory Models on the Example of Enterprises from the Lubelskie and Podkarpackie Voivodeships

ANALIZA PORÓWNAWCZA MODELOWANIA LOGITOWEGO I LINIOWEJ FUNKCJI DYSKRYMINACYJNEJ W OCENIE RYZYKA UPADŁOŚCI SPÓŁEK GIEŁDOWYCH

Repair and Renovation Reserve as a Tool of Commonhold Repair and Renovation Policies in Residential Properties Co-owned by Local Councils in Poland

Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis

The Capacity to Forecast Enterprise Insolvency on the Polish Market Using the Precursory Altman Z-Score Model (1968)

General bankruptcy prediction models for the Visegrád Group. The stability over time

On the binary classification problem in discriminant analysis using linear programming methods

Analiza dyskryminacji w identyfikacji dobrobytu ekonomicznego gospodarstw domowych w województwie podkarpackim

BUSINESS FAILURE PREDICTION MODELS BASED ON EXPERT KNOWLEDGE