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Abstract This article covers the topic of the relationship between the growth of companies and their financial condition when different business profiles are surveyed, such as high-tech, growth potential companies included in the NASDAQ Composite Index and traditional, matured companies included in the Dow Jones Industrial Average (DJIA), commonly known as blue-chip stocks. The hypothesis that the relationship between the Altman Z-score and the growth of enterprises as measured by assets, equity, sales, and earnings per share is positive was tested with Granger and VAR models. The main difference was found to be related to the size of the companies size and dynamics of growth. It was also shown that between NASDAQ enterprises there was no relationship between their growth and Altman Z-score, whereas when the DJIA blue chips were taken into account, a positive relationship was identified. It can be concluded that high-tech enterprises grow in a less predictable way not related to their economic condition, but mature enterprises focused on the growth and their condition. The value added of the article is finding that high-tech companies with growth potential and blue chips are managed in a different way due to their strategies of development.

This article covers the topic of the relationship between the growth of companies and their financial condition when different business profiles are surveyed, such as high-tech, growth potential companies included in the NASDAQ Composite Index and traditional, matured companies included in the Dow Jones Industrial Average (DJIA), commonly known as blue-chip stocks. The hypothesis that the relationship between the Altman Z-score and the growth of enterprises as measured by assets, equity, sales, and earnings per share is positive was tested with Granger and VAR models. The main difference was found to be related to the size of the companies size and dynamics of growth. It was also shown that between NASDAQ enterprises there was no relationship between their growth and Altman Z-score, whereas when the DJIA blue chips were taken into account, a positive relationship was identified. It can be concluded that high-tech enterprises grow in a less predictable way not related to their economic condition, but mature enterprises focused on the growth and their condition. The value added of the article is finding that high-tech companies with growth potential and blue chips are managed in a different way due to their strategies of development. [ABSTRACT FROM AUTHOR]

The prediction of bankruptcy risk poses a formidable challenge in the fields of economics and finance, particularly within the healthcare industry, where it carries significant economic implications. The burgeoning field of healthcare electronic commerce, continuously evolving through technological advancements and changing regulations, introduces additional layers of complexity. We collected financial data from 1265 U.S. healthcare industries to predict bankruptcy based on 40 financial ratios using multi-class classification machine learning models across various industry subsectors and market capitalizations. The exceptionally high post-tuning accuracy rates, exceeding 90%, along with high-performance metrics solidified the robustness and exceptional predictive capability of the gradient boosting model in bankruptcy prediction. The results also demonstrate the power and sensitivity of financial ratios in predicting bankruptcy based on financial ratios. The Altman models highlight the return on investment (ROI) as the most important parameter for predicting bankruptcy risk in healthcare industries. The Ohlson model identifies return on assets (ROA) as an important ratio specifically for predicting bankruptcy risk within industry subsectors. Furthermore, it underscores the significance of both ROA and the enterprise value to earnings before interest and taxes (EV/EBIT) ratios as important parameters for predicting bankruptcy based on market capitalization. Recognizing these ratios enables proactive decision making that enhances resilience. Our findings contribute to informed risk management strategies, allowing for better management of healthcare industries in crises like those experienced in 2022 and even on a global scale. [ABSTRACT FROM AUTHOR]

Copyright of Econder International Academic Journal is the property of Econder International Academic Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Turkish Studies - Economics, Finance, Politics is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study's goal is to evaluate the financial resilience of Bangladesh's ceramics industry using the Altman Z-Score model. The nation's economy heavily depends on the ceramics industry, which also creates jobs and contributes to industrial output. Rapid expansion in both home and international markets makes the financial stability of the sector essential to the stability of the economy as a whole. Using a quantitative methodology, this study examines information from the fiscal years 2020–21 annual reports of five listed ceramics companies. For the first time in this industry context, the Altman Z-Score model reveals a significant portion of companies falling into the "Distress" zone, indicating a heightened risk of financial challenges. The results have real-world ramifications for investors, legislators, and stakeholders. They can be used to improve financial plans and encourage the expansion of sustainable industries. By addressing a significant void in the assessment of financial resilience within Bangladesh's ceramics industry, the study adds to the body of literature.

The Covid-19 outbreak has had a severe effect on the world economy. The company's business operations and profitability are damaged during the covid 19 outbreak. This deterioration is not only threatening the company’s survival position but also destroy the investor’s investment return. Therefore, it is vital to establish an effective early prediction technical method to foresee a corporate distress by a Pro-technical measurement to enhance the corporate sustainability. This study applies Altman Z-Score Model to as a Pro-Technology technique to the financial distress prediction of Malaysia’s Government Linked Plantation Companies (GLC-P) over a period of 10 years starting from 2012 to 2021. The significant contribution of the study is that the Z-Score Model provides an advanced indication tool regarding the financial stability of the respective GLC-P companies. The findings indicate that Financial Distress Prediction was dependent via in-time application of leverage, liquidity, activity, and profitability to the Altman Z-Score Model. Profitability and leverage were found to be superior prediction tool to financial distress.

The Covid-19 outbreak has had a severe effect on the world economy. The company's business operations and profitability are damaged during the covid 19 outbreak. This deterioration is not only threatening the company’s survival position but also destroy the investor’s investment return. Therefore, it is vital to establish an effective early prediction technical method to foresee a corporate distress by a Pro-technical measurement to enhance the corporate sustainability. This study applies Altman Z-Score Model to as a Pro-Technology technique to the financial distress prediction of Malaysia’s Government Linked Plantation Companies (GLC-P) over a period of 10 years starting from 2012 to 2021. The significant contribution of the study is that the Z-Score Model provides an advanced indication tool regarding the financial stability of the respective GLC-P companies. The findings indicate that Financial Distress Prediction was dependent via in-time application of leverage, liquidity, activity, and profitability to the Altman Z-Score Model. Profitability and leverage were found to be superior prediction tool to financial distress. [ABSTRACT FROM AUTHOR]

The phenomenon of financial reporting manipulations and bankruptcy likelihood has always been a topic of interest among researchers. Corporate managers can have the motivation to compromise the financial reporting quality to hide the deteriorating financial health of the firms, nonetheless, if such practices go unabated then such firms can be exposed to serious outcomes in the form of their increased bankruptcy likelihood (Berglund & Makinen, 2016). The abovementioned outcome can be even more threatening in the banking sector due to its inherent nature. The current study aims to examine the impact of financial accounting manipulations on the likelihood of bankruptcy in Nordic banks. Beneish M-score model and Jones model have been applied to evaluate earnings quality, whereas financial distress has been measured by Altman Z-score model (Ebaid, 2022). Based on the analysis of secondary data collected from 33 Nordic banks for the period 2011-2018, the findings disclose that there is an absence of any systematic application of financial accounting manipulations measures, with a few exceptions, by the Nordic banks. Furthermore, there is no evidence to suggest that financial accounting manipulations increase the bankruptcy likelihood of banks. The current study is not only amongst the fewest empirical studies on the said topic conducted in the context of Nordic banks, but it also adds to methodological refinements by including two distinct measures of financial reporting quality to enhance the reliability and robustness of empirical findings. [ABSTRACT FROM AUTHOR]

Copyright of Tesla Revista Científica is the property of Puerto Madero Editorial Academica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of BH Economics Forum / BH Ekonomski Forum is the property of University of Zenica, Faculty of Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The overall objective of this research is to analyze the financial condition of failing companies prior to bankruptcy, in comparison with non-failing companies, which are matched on the industry, size, and timeperiod. The sample consists of 168 SMEs from the wholesale and retail industry, whose financial statements were analyzed for the 2011-2015 period. The analysis is primarily based on the ratio analysis and the models developed for bankruptcy prediction and financial statement manipulation. Mann- Whitney U test is used to compare differences between failing and non-failing SMEs for a set of twenty variables. Research findings indicate that there is a significant difference between failing and non-failing SMEs, especially in accruals, asset quality, leverage, profitability, and liquidity. For the very first time in the transition economy of CEE Bosnia and Herzegovina, the pre-bankruptcy behavior of failing SMEs is analyzed, providing insights into potentially manipulated areas, which represent the main contribution of the research. [ABSTRACT FROM AUTHOR]

The background of this study was based on market share of Isalmic banks in which it is only 5% of National Banks in Indonesia. This indicates ineffective Islamic banks performance. Therefore it will lead to the bankruptcy. Assessing bankruptcy required deep assessment of company performance through its financial ratios; these are Working Capital to Total Assets (WCTA), Earnings Before Interest and Tax to Total Assets (EBITTA), Retained Earnings to Total Assets (RETA) and Book Value of Equity to Book Value of Total Debt (BVEBVTD). The purpose of this study was intended to explain about the influence of those financial ratios on bankruptcy prediction of banks based on Altman Z-Score Model. The data was conducted through indirect observation from quarterly financial report of banks for period 2014-2016. The samples were 11 Sharia banks from 13 Sharia banks listed on Indonesia Financial Services Authority (OJK-RI) by January 2017. The process of analysis was started by conducting Stationery analysis then Regression analysis, the test of assumptions and Multiple Discriminant Analysis (MDA). The result suggests that WCTA, EBITTA and BVEBVTD variable show positive and significance effect on bankruptcy prediction, while the RETA variable shows negative and insignificance. Based on this study, there are only two variables, WCTA and BVEBVTD, that couldpredict bankruptcy with 98.2% accuracy.

In today's era, banks are more serious about their success and survival due to increased Non-Performing Asset (NPA) over a period of time. An increased number of NPA's shows that banks are facing huge credit risk. This calls for a proper assessment of credit risk. There are many techniques available for credit risk assessment and one of the most popular approaches is using a scoring model. In the current paper, Altman Z-score, Springate and Grover and Zmweskis model are applied to assess credit risk of public, private and merged banks. The aim of this paper is to apply and compare these scoring models for credit risk assessment of public, private banks and merged banks in India. The data collected during the period 2005- 2017 were tested 44 Indian banks. The result shows a similarity in Springate and Grover scoring model and has implications in assessment of banks credit risk in India. As per the ranks given by these models, Dena bank and Catholic Syrian bank in case of public and private banks, respectively, achieved the first rank, depicting a highly secured financial position of these banks. [ABSTRACT FROM AUTHOR]

Significance: Banking system affects the economic performance of different country. The failure of one bank has a spillover effect on the other bank and throughout the world economy. In other words, the effect of bank becoming insolvent often leads to adverse consequences for many stakeholders, thus the prediction of bankruptcy may be highly beneficial to the individual bank, Government, Auditors, Creditors, owners, society and other stakeholders. A proper prediction of firm bankruptcies might therefore be extremely important and of grant of interest wide range of relevant financial actors. To avoid the risk of bank failure, banks should find the reliable ways to predict bankruptcy. Method: Literature review shows different methods available for predicting bankruptcy. One of the methods for bankruptcy study is scoring model. Altman Z-score is one of the pioneers in the bankruptcy prediction model Hence present study applied this model on forty four public, and private banks, but due to time factor - the said model lose its importance. When an old original model is applied to a more recent sample the predictive power of the model is very low and the bankruptcy is over predicted. Therefore, the model is recalibrated by changing coefficients using multiple linear regression techniques. Result: The result shows that, recalibrated Altman model performs better than the original Altman model. Conclusion: Thus recalibrated model shows the increased accuracy compared to original Altman model. This proves the work of other researchers who criticizes the original Altman model is not working in the current period. [ABSTRACT FROM AUTHOR]

Prediction of bankruptcy is a critical task. Firms can be hedged from bankruptcy situation by solvency recognition at inceptive stage which may avoid enormity in the near prospective. There are lots of techniques available for measuring the financial health of a business firm wherein Altman's Z-score is one of the prominent measures for predicting bankruptcy. The study is based on the fundamentals of the companies using financial ratios by taking companies of PSU index listed on Bombay Stock Exchange across different sectors over a period of 6 years from 2013-2018. The finding reveals that Altman's Z-score model has a remarkable degree of accuracy in predicting distress using financial ratios. The results may be useful for the managers for financial decision making, the stakeholders to choose investment options & others to look after their interest in the concerned manufacturing and non-manufacturing companies. [ABSTRACT FROM AUTHOR]