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EN
This paper contains an analysis of the level of security of banks operating in Poland, with forms of the ownership taken into account. The results of the analysis have shown specificity of our country when compared to research already published. During volatile conditions in global markets nearly constant level of security of the cooperative banks and high dynamicity of indicators of commercial banks should be pointed out. Both BFG safety and the Z-score indexes lead to the conclusion that the financial crisis has highlighted the weakness of basing the security of banks on apparent, above-average financial results and used leverage, with the simultaneous abandonment of strengthening the capital base and of maintaining quality of loan portfolios.
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Content available remote Discriminatory Power of the Altman Z-Score Model
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EN
This article aims to assess the discriminatory power of one of the most famous and most discussed corporate predictive models, the Altman ZScore. This model ranks among the bankruptcy models, whose main purpose is to detect the impending bankruptcy in good time. The research focuses on three main areas of assessing the discriminatory power of the model. The first part deals with the overall discriminatory power of the model; the second part is aimed at quantifying the impact of individual variables on misclassification of enterprises in bankruptcy. The last part quantifies the discriminatory power of individual variables of the model. The results are compared with the findings of the author of the model. The empirical research is based on the accounting data of Czech companies from the manufacturing industry. Both thriving and bankrupt companies are included in the research.
EN
Research background: Since the turn of the 21st century financial statement manipulations became the center of attention for accountants, auditors and financial analysts. Since being classified by the regulators as fraudulent, earnings management has required a separate detection methodology. The majority of detection research is performed through the comparison of a large number of statements for the same company in order to find irregularities in earnings behavior. Shortening of the detection time and the amount of data becomes important. Purpose of the article: The goal was to compare the characteristics of M-Score and ∆P-∆R and to find their advantages and limitations. Applying both indicators to the different samples, the research attempted to determine the statistical connection between them and to set up the limits of their applicability. Since M-Score indicator is liquidity-based, this research attempted to determine to which extent M-Score and Z-Score are statistically related. Methods: The research paper compares the behavior of both indicators using various samples of financial data: the sample of companies, charged with fraud, the sample with exceptional liquidity, the large random sample and the sample from the emerging market economy. Based on the original observations, two other subsamples (one based on poor Z-Score and one based on exceptional Z-Score) were extracted from the main sample. For all samples ∆P-∆R, M-Score and Z-Score were statistically compared among and between themselves. Findings/value added: The research found the limitations of ∆P-∆R and M-Score in the stable markets and was able to connect them in the emerging market by using linear regression model (also including Z-Score). The research confirmed that M-Score can mistake exceptional performance for manipulations, resulted in Type I errors. ∆P-∆R appeared somewhat coarse and prone to Type II errors. The combined use of both in the emerging markets will provide the best approach.
PL
Wprowadzenie. Tkanka kostna jest tkanką aktywną metabolicznie, która podlega dynamicznym przeciwstawnym procesom kościotworzenia i resorpcji. Coraz większą uwagę zwraca się na znaczenie aktywności fizycznej jako czynnika warunkującego zdrowy układ kostny. Cel badania. Celem badania była ocena zawartości mineralnej (BMC) i gęstości tkanki kostnej (BMD) oraz wskaźników T-Score i Z-Score: całego szkieletu, kręgosłupa lędźwiowego i nasady bliższej kości udowej prawej i lewej młodych osób w zależności od aktywności fizycznej. Materiał i metoda. W badaniu udział wzięło 120 osób w wieku od 20 do 29 lat – (60 kobiet i 60 mężczyzn), w tym po 60 osób (30 kobiet i 30 mężczyzn) w grupie bardziej aktywnych i mniej aktywnych fizycznie, którzy w badaniu zostali określeni jako nieaktywni fizycznie. Oceniane parametry uzyskano przy użyciu densytometru Lunar iDXA (GE Healthcare). Analizie poddane zostały następujące parametry: BMC, BMD, T-Score i Z-Score całego szkieletu, odcinka L1-L4 kręgosłupa lędźwiowego i nasady bliższej kości udowej prawej i lewej, a także BMI i BSA. Wyniki. Uzyskano wyższe wartości ocenianych parametrów w grupie aktywnych fizycznie w porównaniu z grupą nieaktywnych fizycznie. Istotnie statystyczne różnice uzyskano dla: a) BMD i BMC całego szkieletu oraz BMC odcinka L1-L4 kręgosłupa lędźwiowego i nasady bliższej obu kości udowych, porównując obie grupy bez podziału na płeć; b) BMD i BMC oraz T-Score całego szkieletu i Z-Score odcinka L1-L4 kręgosłupa lędźwiowego tylko w grupie kobiet. Analizując korelację między BMI a BMD oraz BSA a BMD całego szkieletu, stwierdzono istotnie statystyczne dodatnie korelacje w obu grupach bez podziału na płeć oraz w grupie mężczyzn. Natomiast istotność statystyczną wykazano dla różnicy współczynników korelacji pomiędzy grupami dla korelacji BMI i BMD total. Wnioski. Uzyskane w prezentowanej pracy wyniki wskazują, że nawet niewielki, regularny wysiłek na poziomie rekreacyjnym wpływa na zwiększenie gęstości kości.
EN
Introduction. Bone tissue is a metabolically active tissue that undergoes dynamic opposing processes of bone formation and resorption. More and more attention is paid to the importance of physical activity as a determinant of a healthy skeletal system. Aim. The aim of the study was to assess the bone mineral content (BMC) and bone tissue density (BMD) as well as the T-Score and Z-Score indicators: of the whole skeleton, lumbar spine and proximal femoral right and left femurs in young people depending on physical activity. Material and methods. 120 people aged 20 to 29 (60 women and 60 men) took part in the study, including 60 people (30 women and 30 men) in the more active group and less physically active people who were described as physically inactive in the study. The evaluated parameters were obtained using a Lunar iDXA densitometer (GE Healthcare). The following parameters were analyzed: BMC, BMD, T-Score and Z-Score of the whole skeleton, the segment L1-L4 of the lumbar spine and the proximal epiphysis of the right femur and left, as well as BMI and BSA. Results. Higher values of the assessed parameters were obtained in the physically active group compared to the group of physically inactive. Significant statistical differences were obtained for: a) BMD and BMC of the whole skeleton and BMC of the L1-L4 segment of the lumbar spine and proximal epiphysis of both femurs comparing the two groups without gender division; b) BMD and BMC as well as T-Score of the whole skeleton and Z-Score of the L1-L4 segment of the lumbar spine only in the group of women. Analyzing the correlation between BMI and BMD as well as BSA and BMD of the whole skeleton, statistically significant positive correlations were found in both groups without division into sex and in the group of men. On the other hand, statistical significance was demonstrated for the difference in correlation coefficients between the groups for the correlation between BMI and BMD total. Conclusions. The results obtained in the presented study indicate that even small, regular exercise at the recreational level increases bone density.
5
Content available remote Data Mining for Bankruptcy Prediction: An Experiment in Vietnam
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EN
In the history of the world economy, the bankruptcy of some large companies has caused global financial crises. The study aimed to postulate a model of bankruptcy prediction for listed companies on Vietnam's stock market. The research used six popular algorithms in data mining to predict bankruptcy risk with data collected from 4693 observations in the period 2009-2020. The research results showed that Logistic algorithms, Artificial Neural Network, Decision Tree have a high level of predicting bankruptcy with an accuracy of 98%. The study identified the three most important indicators: inventory turnover ratio, debt to equity ratio, and debt ratio that affect the corporate bankruptcy prediction. The study showed the threshold points of 10-indicators to avoid bankruptcy likelihood. These results recommended that the model could be applied in practice to reduce risks for businesses and investors in the Vietnamese market.
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