Insolvency Risk. Application of Altman Z-Score to the Auto Parts Sector in Romania (original) (raw)
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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.
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.
Evaluation of the revised Z'-score model as a predictor of a company's financial failure
BH Ekonomski forum
Under contemporary business conditions, there are numerous models used for the assessment of a company's financial situation and the prediction of the likelihood of its bankruptcy. These models have been mainly developed using the company's financial information. One of them is the Altman Z-score model. The model separates financially successful and stable companies from those having difficulties in business and headed for bankruptcy. This paper explains the importance of prudential information, basic financial statements and financial indicators and presents the research aimed at evaluating the applicability of the revised Altman Z'-score model in the Federation of Bosnia and Herzegovina (FBiH). Based on financial information, the paper analyzes the business activities of 50 large manufacturing companies in FBiH. The revised Z'-score model achieved a relatively good result in assessing the companies with business difficulties as it correctly classified 10 out of 20 ...
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.
Predicting Bankruptcy: The Altman Z-Score Model, a Multi-purpose Tool that Requires Cautious Use
International Corporate Rescue, Vol. 12, Issue 5., 2015
Although businesses may have varying purposes, the main objective is the same for all of them and it is simply avoiding bankruptcy. Since a company’s bankruptcy is critical for not only its stakeholders but also for the oth- er parties such as its suppliers and creditors, the ability to diagnose the problems of a company in advance is a very valuable asset. The models that provide the ability to predict bankruptcy are important from the national economy perspective as well, since the employment of them is a precondition for guaranteeing the soundness and stability of the banking system and paving the way for incentive compatible, risk sensitive behaviour of debtors.
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%.
Dinasti International Journal of Economics, Finance & Accounting
This study aims to identify and examine the condition of financial distress in the automotive component industry issuers in the period 2014 ~ 2018, using the Altman Z-score, Springate S-score, Ohlson O-score, and Zmijewski X-score against financial ratios as an analysis form of company management to predict the early warnings of company bankruptcy. This study uses quantitative, secondary, and panel data; while the sample uses a non-probability boring sampling technique of 11 companies. The results showed that these four models can predict financial distress by identifying each model. Altman’s model found 8 distress zone points, 16 grey zone points, and 31 safe zone points. Springate’s model found 37 points in the distress zone, and 18 points in the safe zone. Ohlson's model found 3 points in the distress zone, and 52 points in the safe zone. Zmijewski's model found only 1 point in the distress zone
WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS, 2020
Bankruptcy is the conclusive affirmation of the inability of a company to support and endure current operations given its current financial position and debt obligations. If bankruptcy could be expected with affordable precision ahead of time, managers and investors of companies may have the possibility to take action to secure their companies, reduce risk and loss of business and perhaps even avoid bankruptcy itself. The aim of this paper is to test the suitability and predictive accuracy of the Altman Z-Score model in the Albanian manufacturing industry. After performing the empirical analysis, the conclusion is that this model clearly fails to effectively predict financial distress and bankruptcy and it isn't reliable in our case. Lastly, a logistic regression model is proposed, which is more adequate for the Albanian context.