scholarly journals Could the Altman Z-score model detect the financial distress in Ghana? Multivariate discriminant analysis

2020 ◽  
Vol 4 (2) ◽  
pp. 8-19 ◽  
Author(s):  
John MacCarthy ◽  
Richard Amoasi-Andoh

The purpose of this paper is to assess the effectiveness of the Altman Z-score model to discriminate between financially distressed and non financially distressed manufacturing firms listed on the Ghana Stock Exchange. Eleven firms consisting of two financially distressed and nine non-financially distressed manufacturing firms were analysed. Independent descriptive statistics, independent sample t-test, and multivariate discriminant analysis were the analytical tools used to analyse the hypotheses of this study. The study revealed that working capital/total assets and sales/total assets were the major discriminators of financially distressed firms on the Ghana Stock Exchange. Multivariate discriminant analysis revealed an accuracy rate of 79.9% to detect financially distressed firms in Ghana.

2019 ◽  
Vol 7 (1) ◽  
pp. 63-72
Author(s):  
Alhassan Musah ◽  
Josephine Agyimaa Agyirakwah

The study examined the applicability of the Altman Z-score model in predicting bankrupt companies or financially distressed companies on the Ghana Stock Exchange. A sample 10 listed firms were selected and one other company to be used for validation purposes. The validation process involved data for 2016 and 2017 for Aluworks which represented a distressed company and GOIL Ghana Limited which represented non-distressed company. The final analysis was based on a random sample of 10 listed firms using their 2017 financial statement. The results of the initial prediction showed 50 percent of the companies were correctly predicted whiles the others were misclassified. Additional analyses showed that the size of the company influence the probability of bankruptcy whiles the nature of the business does not. The conclusion drawn shows that the Altman Z-score cannot accurately predict financially distressed firms in Ghana but can still be useful in giving signals.


2017 ◽  
Vol 5 (2) ◽  
pp. 313-321 ◽  
Author(s):  
Anandasayanan S ◽  
Subramaniam V.A

Bankruptcy is the legal status for an individual or company incapable to pay off outstanding debt. Predication of Bankruptcy is critical task. Early stage of identification of likelihood of solvency may avoid evils in the near future & may shelter the firm from Bankruptcy situation. Bankruptcy of organizations can be predicated by using Altman’s Z-Score Model. This study tries to apply the model to understand the likelihood of Bankruptcy of selected listed manufacturing firms for past 5 years from 2010 to 2014 which are listed in Colombo Stock Exchange. The study reveals that four companies completely belong to Safe Zone for the entire period of study. Three firms are in Distress Zone which clearly indicates that these firms may go Bankrupt in near future.


2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Himmiyatul Amanah Jiwa juwita

This study aims to determine the level of corporate bankruptcy using model analysis Altman Z-Score on pharmaceutical companies in Indonesia Stock Exchange (IDX) 2012-2014. The study population was all of the Pharmaceutical Industry with a sample of eight pharmaceuticalscompanies in the Indonesia Stock Exchange (IDX) in accordance with predetermined criteria. The results of this study indicate that the Altman Z-Score model can be implemented to detect the possibility of bankruptcy in the pharmaceutical company in Indonesia Stock Exchange (IDX). Altman Z-Score model and discriminant analysis do not have the same results in predicting bankruptcy in eight pharmaceutical companies because there is a miss classification in one company out of eight companies. The results of the Z-Score using discriminant analysis is able to classify a pharmaceutical company in two groups, that are healthy and gristle to bankruptcy.Keywords: pharmaceutical company, Bankruptcy Prediction, Altman Z-score model


2019 ◽  
Vol 4 (2) ◽  
pp. 298
Author(s):  
Yunan Surono ◽  
Sindy Dwiroro Pangestu

This research aims to prove the financial performance of Manufacture sector with Multiple Discriminant Analysis Bankruptcy Model when measured using the Altman's Z-score first model, Altman's Z-score revision and Altman's Z-score modifications, Springate model and Zmiejewski model as well as to get the stocks that have the best performance based on the model. In this research the population used is the stock sector manufacturing group on the Indonesia Stock Exchange in the year 2014 – 2017 as many as 166 issuers manufacture. This research sample is the manufacture sector company, which provides complete data, and has a total asset of positive value and fluctuates as many as 22 companies. This form of research is an explolanatoris research (explanatory Research). The results showed, that based on the first Altman's Z-score model, in 2014 the company's performance in a healthy or not bankrupt category was 31.82%, while the company had a gray performance of 22.73%, as for The company's performance with the category broke by 45.45%. In 2015 the company's performance with a healthy category of 27, 27, 82%, a company that had a gray performance of 27.27%, the company's performance of the category went bankrupt by 45.45%. In 2016 the company's performance with a healthy category of 22, 73, 82%, the company had a gray performance of 36.36%, as for the performance of the company with the category bankrupt by 36.36%. In 2017 the company's performance with a category of 40.91%, the company has a gray performance of 22.73%, as for the performance of the company with the category bankrupt by 36.36%. Based on the model Altman Z-Score revision can be concluded that in 2014 the company's performance with a healthy category of 31.82%, a company that has a gray performance of 54.55%, as for the performance of the company with the category bankrupt 13.64%. Year 2015 the performance of the company with a healthy category of 27.27%, the company has a gray performance of 54.55%, the company with the category went bankrupt by 18.18%. Year 2016 the company's performance with a healthy category of 45.45%, while the company has a gray performance of 36.36%, the company with the category went bankrupt by 18.18%. Year 2017 the performance of the company with a healthy category of 50.00%, the company that has a gray performance of 31.82%, the performance of the company with the category bankrupt by 18.18%. Based on the model of Altman Z-score modification can be concluded, namely in 2014 the performance of the company with a healthy category of 72.73%, the company that has a gray performance of 22.73%, as for the performance of the company with the category bankrupt of 4.55%. In 2015 the company's performance with a healthy category of 72.73%, while the company had a gray performance of 18.18%, as for the company's performance in the category went bankrupt by 9.09%. In 2016 the company's performance with a healthy category of 77.27%, the company had a gray performance of 13.64%, the company's performance in the category went bankrupt by 18.18%. In 2017 the company's performance with a healthy category of 81.82%, while the company had a gray performance of 13.64%, as for the company's performance in the category went bankrupt by 4.55%. Based on Springate model can be concluded, namely in 2014 the performance of the company with a healthy category of 59.09%, while companies that have a gray performance is not there, as for the performance of the company with the category bankrupt by 40.91%. In 2015 the company's performance with a healthy category of 50.00%, while companies that had a gray performance did not exist, the performance of the company with the category went bankrupt by 50.00%. In 2016 the company's performance with a healthy category of 59.09%, while companies that have a gray performance does not exist, as for the performance of the company with the category bankrupt by 40.91%. In 2017 the company's performance with a healthy category of 63.64%, while companies that have a gray performance does not exist, as for the performance of the company with the category bankrupt by 36.36%. Based on Zmiejewski model can be concluded, in 2014 to 2017 the performance of companies with a healthy or not bankrupt category is 100%, while companies that have a gray performance does not exist, as for the performance of the company with Bankruptcy category does not exist. Stocks that have the best performance based on each multiple discriminant analysis bankruptcy models respectively, namely INTP, CEKA, MERK, GGRM, LMSH, CPIN, MLBI, IKBI, TRIS UNIC and INDF, who have never experienced bankruptcy or in financial distress.


1994 ◽  
Vol 108 (1) ◽  
pp. 39-60 ◽  
Author(s):  
Luigi Giusto Spagnoli ◽  
Alessandro Mauriello ◽  
Giampiero Palmieri ◽  
Giuseppe Santeusanio ◽  
Ada Amante ◽  
...  

2017 ◽  
Vol 133 ◽  
pp. 96-103 ◽  
Author(s):  
Leandro S.A. Pereira ◽  
Fernanda L.C. Lisboa ◽  
José Coelho Neto ◽  
Frederico N. Valladão ◽  
Marcelo M. Sena

2018 ◽  
Vol 10 (8) ◽  
pp. 181 ◽  
Author(s):  
Sufian Al-Manaseer ◽  
Suleiman Al-Oshaibat

This paper aims to investigate the Validity of Altman z-score model to predict financial failure in insurance companies listed on Amman Stock Exchange (ASE) over the period 2011-2016. To achieve the goal of the study, the study depended on the different statistics analytical method and Multiple Linear Regression through doing the statistical analysis of the independent variables on the dependent variable related to the subject of the study through the (E-views) program in order to cover the analytical part of the study, in addition to the descriptive method through relying on books, periodicals, previous studies and financial reports of the insurance companies of the study’ sample, whether the direct or the indirect ones, to cover the theoretical part. The result of the study finds a high predictive power for Z-score model. Moreover, the findings reveal that Z-Score model could be valuable instrumental indicators for many users of financial statement such as financial managers, auditors, lenders, investors, to make right decisions in the face of financial failure.


2018 ◽  
Vol 2 (1) ◽  
pp. 121-128
Author(s):  
Barcha Handal Sakti ◽  
Ely Kartikaningdyah

This research aimed to know whether the predictor variables on Bhandari’s z-score model having discriminating power which in each of the group has significant difference. Sample which was being used to assist was the manufacture company that consisted of healthy company and the unhealthy company enrolled in Indonesia stock exchange in the period of 2012-2014. Sample collecting method used purposive sampling and cross section was the data used in this research. This research was conducted by using Multivariat Discriminant Analysis (MDA). The result of this study showed predictor variable that gave discriminating power which stood of quality of earning (EAQ), operating cash flow divided by current liabilities (OCFCL), operating cash flow margin (OCFM), and operating cash flow return on total assets (OCFA) in distinguishing the healthy and unhealthy company significantly.


2019 ◽  
Vol 4 (01) ◽  
pp. 27
Author(s):  
Indar Khaerunnisa ◽  
Nur Anisa Rahayu

This research aims to figure out the level of companies bankruptcy by applying Altman Z-Score at the manufacturing companies registered in the Indonesia Stocks Exchange. The result of the research has indicated that ZScore model is applicable to detect the company’s potential bankruptcy issues, especially manufacturing company subsectors of cosmetics and houseappliances. Altman Z-Score model has classified the companies into three categories; safe, grey area and distress. Based on the result of the research, for the companies which are in the grey area category are suggested to improve their financial performance and to use the benefit of all the assets properly to get the revenue as much as possible. However, for the companies which are in the safe category are suggested to increase their performance, especially marketing performance so that they will receive bigger amount of the revenue, nevertheless, the potential of financial distress can be minimized accordingly. Keywords: manufacturing company, financial distress, Altman Z-Score.


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