Evaluation of the revised Z'-score model as a predictor of a company's financial failure (original) (raw)
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PREDICTING BANKRUPTCY OF SELECTED FIRMS BY APPLYING ALTMAN'S Z-SCORE MODEL
Financial health is of great concern for a business firm. For measuring the financial health of a business firm, there are lots of techniques available. However, Altman's " Z-score " has been proven to be a reliable tool. This model envisages predicting the possibilities of bankruptcy of manufacturing organization. The " Z score " analysis has been adopted to monitor the financial health of the company. The current study has been conducted to assess the financial health of firms namely Hindustan Uniliver Ltd, Colgate Palmolive, Nestle, ITC and P&G. All the above companies are manufacturing firms. The research used secondary data from the financial reports of five manufacturing companies for a period of the five years from 2013 to 2017. The study reveals that none of the companies completely belongs to Safe Zone except for few years. Most of the firms are in Distress Zone which clearly indicates that these firms may go Bankrupt in near future. 1) Introduction The objective of all organizations is to create and increase shareholder value. All stake holders, including banks, financial institutions, regulatory bodies, the government, suppliers, customers, etc. want them to do well and be effectively and efficiently managed to prevent driving them to the brink of business failure/bankruptcy and then pushing them to failure, if mismanagement continues. To achieve profit maximization objective, firm needs strong internal & external support. Bankruptcy is a situation where the firm's total liabilities exceed total assets. The real net worth of the firm is, therefore negative. This leads to reduced sales, increased cost & losses, ineffective competition etc. Ultimately firm is under distress stage. Under such situations it becomes difficult for investors & lenders to analyze the financial performance of the organization. Several bankruptcy models for example, logit analysis, recursive portioning algorithm and neural networks are available but still Altman's model is considered to be superior and pervasively applied by researchers all over the world in the present days. Altman's Z-Score Model is the output of a credit-strength test that predicts company's likelihood of bankruptcy. 2) Literature Review Sanesh (2016) tried to assess the Altman Z-score of NIFTY 50 companies excluding banks and financial companies. The score tries to predict probability of default by the companies due to the financial distress based on the current financial statistics of the company. Kumari's (2013) paper tried to predict bankruptcy for MMTC based on Altman's model of the Z score. She concluded that the overall financial health of MMTC is good, and it can be quoted as an investor friendly company. Ramana Reddy and Hari Prasad Reddy (2013) is also relevant. In this article, the Z score analysis shows the poor financial performance leading to bankruptcy of Chittoor cooperative sugars Ltd. Comparatively the financial performance of Sri Venkateswara Sugars Factory Ltd. was good. Vikas Tyagi (2014) in his paper investigated the financial health of logistic industry in India based on Z score analysis. It reveals that Indian logistic industry was healthy industry .It is good that average Z score value increases from 2006 to 2010 (2.54 to 3.01) when Indian economy was hit by global recession. This indicates the overall performance of Indian logistic industry was good. Al-Rawi, Kiani and Vedd (2008) used the Altman z-score analysis to predict a firm's insolvency. They have remarked that the firm has increased its debt and face bankruptcy in the near future. Mizan and Hossain's (2014) study has been conducted to assess the financial health of cement industry of Bangladesh. The study revealed that among the five firms, two firms are financially sound as they have higher Z score than the benchmark (2.99). Another firm is in the grey area that is the firm is financially sound, but the management requires special attention to improve the financial health of the organization. The other two firms are at serious risk of financial crisis. Gerantonis Vergos and Christopoulos (2009) investigated whether Z-score models can predict bankruptcies for a period up to three years earlier. Results showed that Altman model performed well in predicting failures. They concluded that the results can be used by company management for financing decisions, by regulatory authorities and by portfolio managers in stock selection. Alkhatib and Al Bzour (2011) conducted a study to report the effect of financial ratios in bankruptcy prediction in Jordanian listed companies through the use of Altman and Kida models. They suggested that the Jordanian listed companies should at least apply one of these models with high credibility for predicting corporate bankruptcy. Among others, corporate bankruptcy prediction model developed by Altman in 1968 is the most accepted and widely used tool (Mizan, Amin and Rahman 2011).The Altman Z score model is used in different countries for predicting bankruptcy.
Australasian Accounting, Business and Finance Journal, 2016
Financial health is of great concern for a business firm. For measuring the financial health of a business firm, there are lots of techniques available. But Altman's Z-score has been proven to be a reliable tool. This model envisages to predict the possibilities of bankruptcy of manufacturing organization. Multiple discriminate analyses (MDA) are useful tools in such situations. The use of MDA helps to consolidate the effect of all ratios. Keeping the above view in mind, the "Z score" analysis has been adopted to monitor the financial health of the company. The current study has been conducted to assess the financial health of a firm namely Raysut Cement Company SAOG and its subsidiaries in Oman. This study was based on the secondary data which was obtained from the published sources i.e. Annual report for the period of 8 years (2007 to 2014). The study revealed that the Company Raysut Cement Company SAOG and its subsidiaries are financially sound as they have higher Z score than the benchmark (2.99) except in some years of study. The findings of the study may be useful for the managers to take financial decision, the stockholders to choose investment options and others to look after their interest in the concerned cement manufacturers of the country.
Financial sustainability of a business is one of the prime concerns for both internal and external stakeholders. Internal stakeholders such as managers and employees might be interested in whether their efforts in the business add value and secure their job, while external stakeholders might be concerned directly with their Abstract Key Words: Whether a company would survive in a highly competitive business environment depends upon some important factors, viz., (1) financial strengths at the inception of the business, (2) ability of the company to generate sufficient cash flows from its continuing operations, (3) company's access to capital markets, (4) investors' trust on the growth of the company, and (5) the company's financial solvency to face adverse situation. Eventually, as financial health of a company continues to decline, the solvency gauges automatically a warning light to the stakeholders. From this perspective, the current study aims to investigate the likelihood of financial distress of leading pharmaceutical companies in Bangladesh, listed under category " A " of Dhaka Stock Exchange (DSE). The study provides some valuable insights to the stakeholders about financial fundamentals of the selected firms in addition to the critical focus on their bankruptcy possibility. For bankruptcy prediction of the selected firms, the study has applied the widely accepted Altman Z-score model. The study has also performed a trend analysis of some important financial variables in order to assess the companies' financial health. The empirical analysis reveals some valuable findings. According to the values of Z-score, two firms (Square Pharmaceutical and IBN SINA Pharmaceutical Industry) are found financially sound having no bankruptcy possibility in near future, of which the former is found exceptionally out performer in the medicine industry. The values of Z-score and other financial trend analysis of the rest of the companies are found to be unsatisfactory and they have significant likelihood of facing financial distress in near future.Another important finding of the study is that market value of equity of most of the selected firms is not reflecting the respective companies. This may be a major concern to the general investors and other stakeholders as well. Bankruptcy, Z-score, Dhaka Stock Exchange (DSE), Financial Health.
Journal of Applied Management and Investments (ISSN 2225-3467) - Ukrain, 2013
In this case study, we used both Altman's Z-score and Modified Z”-score models to investigate whether it is possible to rely on Altman’s Models (1968, 1983) to assess financial health and predict financial failure of a publicly traded non-manufacturing company in India. The findings of this case study indicated that the Altman's original Z-score model predicted that the financial health of the firm under consideration is not consistent over a period of 2005 - 2012. The same is confirmed by the Revised Z”-score model as well. According to this study, the models were able to predict financial distress and probable future bankruptcy of the firm. The mean Z-score for the firm under investigation during the period 2005-2012 is 0.918 and the mean Z”-score for the same period is 0.019, both being less than cut-offs confirm poor financial health of the firm and that the bankruptcy is very likely to happen if no corrective actions are taken by the management in near future.
Relationship between the Altman Z-Score model and the Z-Score financial indicators
From a theoretical point of view, there is no general consensus on the identification of the financial difficulties of a company. The Altman Z-Score model is recognized in the literature as an indicator for measuring the probability of financial insolvency. While this model is widely used as a metric for predicting financial distress, there is no agreement on the factors that determine the behavior or outcome of the Z-Score. In this sense, the purpose of this study is to analyze the factors that determine the behavior of the Z-Score in Colombian companies. The research is developed under a quantitative methodological approach, with a correlational design. This research scope seeks to measure the association between the Altman Z-Score and the financial indicators that determine its outcome; for this purpose, it is analyzed a total of 2,684 companies of the Colombian commercial sector that reported financial information on a systematic basis during the period 2016-2020. The results of the statistical tests carried out reveal that there is a direct relationship between the indicator that measures the financial structure (equity/liabilities) and the Altman Z-Score. This leads to the conclusion that, from the point of view of Altman’s model, a company that seeks to capitalize profits and keep debt levels under control will be a company with financial stability and a low probability of financial insolvency.
Diponegoro International Journal of Business, 2021
The purpose of this study is to determine differences in bankruptcy predictions of the Altman and Foster models. The sampling technique used is purposive sampling with an observation period of 2016-2018 with 12 company samples per year. The analysis technique uses the Altman and Foster method with the paired two-sample t-test as a hypothesis test tool. Based on the results of the Altman and Foster Z- Score model of automotive and component industries in 2016-2018 it can be concluded that the financial model of Altman and Foster can predict bankruptcy. Furthermore, the hypothesis testing found that there is no differences in the results of the Altman and Foster bankruptcy prediction.
Over the years, serious attention has been to bankruptcy prediction models and the problems associated with predicting failure in corporate firms. Corporate failure prediction has become a very vital issue in finance especially given the fact that so many researchers have given so many different types of prediction model. In addition, the multiple discriminant analysis seems to be the best model that achieves a very high result of accuracy levels. In this study, 34 public listed manufacturing companies in Malaysia where used from 2010-2014. Companies were chosen from companies listed under the PN17 companies while healthy companies where matched using paired sample t-test using random stratified sampling method. Initially, the main aim or objective of this study was to examine the reliability and relationship of Altman' Z-score model to corporate failure and to investigate if all failing companies where listed under the PN-17 on the Kuala Lumpur stock exchange (KLSE) now popularly known as Bursa Malaysia. Findings showed that not all failed companies where listed under PN17 companies in bursa Malaysia. While all but o ne of the companies under the PN17 companies where in the safe zone in the fifth year. The Study findings showed four out of five financial ratios where significantly related in the prediction of corporate failure under the Z-score model. Also the regression analysis showed that the model is a great fit with significance of 0.000 and accuracy levels of 86% and 99.6%.
The purpose of this study was to analyze financial distress conditions in Bakrie Group companies listed on the Stock Exchange in the 2012 to 2017 period. The data used in this study is secondary data, taken from the company's financial statements on the IDX in 2012-2017. The sample consists of 5 companies from 2012 to 2017 and is still registered to date. The method used is the original Altman Z-Score model for manufacturing public companies. The ratio used is working capital (working capital to total assets (total assets), retained earnings (retained earnings) to total assets, earnings before interest and taxes (EBIT) to total assets, the market value of the capital of the debt value (market value of total liabilities) , and sales to total assets ( sales to total assets ) .The results of the study show that the five companies are in a distress zone where the factors are significant because the average profitability and low liquidity of the company cannot be economically and efficiently run his business.
Insolvency Risk. Application of Altman Z-Score to the Auto Parts Sector in Romania
International Journal of Innovation and Economic Development, 2020
This paper intends to apply the Altman Z-score model to all the companies active in the wholesale of motor vehicle parts and accessories (NACE 4531), with extended financial statements. Using the panel data model over the time series for 2008-2016 on the companies of this sector, we conclude that 99% of the Z-score is explained by the independent variables (working capital, capital structure, turnover, earnings before interest and tax), with estimated parameters very close to the model`s classical values. The sample description of the paper and the corresponding results highlight the Z-score evolution by turnover clusters and principal components, with the largest companies performing the best (the only cluster with Z-score median above 3). We notice a tendency for decreasing high-risk companies and increase in the medium risk companies, whereas the low-risk companies are relatively stable. This improvement is mostly due to the increasing capitalization rate and less external debt, ...
Open Journal of Accounting, 2013
This study examines the efficacy of Z-Score and operating cash flow as Corporate Insolvency prediction models in developing cash economy. The research specific objectives are to determine the predictive efficacy of Z-Score and operating cash flow in discriminating between would fail and going concern companies, identify more effective model for predicting Corporate Insolvency between Z-Score and operating cash flow and assess the predictive ability across industries of the two models. Sixty-two corporate financial statements possessing flow-based insolvency symptoms were tested. Tools of analyses employed are ANOVA, Loglinear Analysis, Fredman ANOVA and Percentages. Z-Score predictive ability across Services and Merchandising sectors is found to be very poor but very strong on Manufacturing and Oil Services, while Operating Cash Flow model is found to be more effective in predicting accurately Service and Merchandising Sectors. The predictive efficacy of the two models significantly varies as the year becomes closer to the year of corporate failure. It is recommended that across industrial sectors, Z-Score model should be used for testing business failures in Manufacturing and Oil Services while Operating Cash Flow model is better employed in solvency stress test for Merchandising, Transport & Aviation and Service industrial sectors.