scholarly journals Distressed Firm and Bankruptcy Prediction in an International Context: A Review and Empirical Analysis of Altman's Z-Score Model

Author(s):  
Edward I. Altman ◽  
Malgorzata Iwanicz-Drozdowska ◽  
Erkki K. Laitinen ◽  
Arto Suvas
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.


Owner ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 343-355
Author(s):  
Muhammad Yunus ◽  
Calen Calen ◽  
Sarida Sirait

This study aims to determine the effect of the bankruptcy prediction of the Altman z-score model, auditor reputation and opinion shopping on going concern audit opinion in manufacturing companies listed on the Indonesia Stock Exchange in 2015-2019. This research is a causal associative research with a quantitative approach. The sample in this study were 25 manufacturing companies listed on the Indonesia Stock Exchange which were determined using purposive sampling technique. Observations in this study were carried out throughout the period 2015 to 2019 so that the number of observations was 125 data. The type of data used in this study is secondary data. While the data analysis method used in this research is panel data regression analysis with statistical data processing software, namely STATA. Based on the results obtained in this study, it can be seen that the prediction of bankruptcy based on the Altman z-score model has no significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange. Auditor reputation is proven to have a negative and significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange. And opinion shopping is also proven to have a negative and significant effect on going concern audit opinion on manufacturing companies listed on the Indonesia Stock Exchange.


Author(s):  
Wong Ming Nok

We make comparison between 6 models including (1) Altman’s (1968) z-score; (2) Model 1: z-score model with adjusted coefficients; (3) Model 2: z-score model with modified variables; (4) Model 3: dynamic logic model; (5) Merton distance to default (DD) model (Bharath & Shumway, 2008) and (6) back-propagation network model (Lippman, 1987). We assess the relative information content of these models regarding their bankruptcy prediction capability. Our tests show that dynamic logic model and DD model both provide significantly more information than the others while DD model has the highest prediction accuracy in the out of sample test. It is also worth noticing that altering coefficients and adjusting variables of the original z-score model could not significantly improve the predictive power of z-score model regarding companies in the industrial industry in the UK.


2017 ◽  
Vol 2 (02) ◽  
pp. 11
Author(s):  
Irwansyah .

This study was conducted to prove the accuracy of bankruptcy prediction of Altman Z-Score model on conventional banks listed on the Indonesia Stock Exchange. The data used in this study is secondary data obtained from the annual financial statements of conventional banks during the period of 2013-2016 mentioned on the official website of the Indonesia Stock Exchange. The data analysis technique used is bankruptcy prediction of Altman Z-Score model, using five variables representing liquidity ratios X1, profitability ratios X2 and X3, and activity ratios X4 and X5. The formula Z-score = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + X5. When Z-Score criteria is Z > 2.90 it is categorized as a healthy company. Z-Score between 1.23 to 2.90 is categorized as a company in area. While Z-Score Z < 1.23 is categorized as a potential bankrupt company. Based on the results of the research, Z-Score analysis that has been done in the period of 2013-2016 indicating that most conventional banks are predicted bankrupt. The lowest score of the Z-Score is 1.23. Only one Bank Jtrust Indonesia Tbk (BCIC bank code) is in a healthy category. Bank Mandiri (Persero) Tbk with BMRI bank code, has been increasing from the prediction of bankruptcy category to the prediction of gray area category.Keywords: Altman Z-Score, Conventional Banks Listed on BEI 2013-2016, Prediction of Bankruptcy.


2021 ◽  
Vol 3 (3) ◽  
pp. 95-106
Author(s):  
Erik Priambodo ◽  
Augustina Kurniasih

This study aims to prove whether coal mining sector companies have the potential to go bankrupt if measured using the Altman Z-Score model. The study also analyzed the effect of the components of financial ratios in the Altman Z-Score model on stock prices. The research sample is 17 coal mining companies listed on the Indonesia Stock Exchange for the 2015-2019 period. The results of the calculation of the Z-Score value show that several coal mining companies have the potential to go bankrupt. Using the panel data regression approach, it was found that the Z-Score value had a significant effect on stock prices. Partially, the EB/TA ratio has a significant effect on stock prices. The ratios of WC/TA, RE/TA, and MVE/BVL have no significant effect on stock prices.


2021 ◽  
Vol 9 (1) ◽  
pp. 84
Author(s):  
Rosmayana Rusman

Bankruptcy is a critical issue that companies must be aware of. Bankruptcy and the level of the company's performance can be seen from the company's financial condition by analyzing the company's financial statements. The most widely used bankruptcy prediction model is the Altman Z-Score model..The Altman Z-Score model analysis was chosen as the model used in bankruptcy prediction because, this model is easy to use with a high degree of accuracy. The purpose of this research is to determine bankruptcy predictions using the Altman Z-Score model in retail companies listed on the IDX in 2014-2018. This kind of exploration is expressive quantitative utilizing monetary reports as an examination instrument. The examining method was,carried out by utilizing purposive sampling,technique which was then controlled by nine retail organizations as the sample. The results show that on average six companies are in a safe zone, including issuers ECII, HERO, MPPA, RANC, SKYB, SONA and two companies in the gray zone or prone to bankruptcy, namely CENT and KOIN, one company in the dangerous zone, namely RIMO


Author(s):  
Wong Ming Nok

We make comparison between 6 models including (1) Altman’s (1968) z-score; (2) Model 1: z-score model with adjusted coefficients; (3) Model 2: z-score model with modified variables; (4) Model 3: dynamic logic model; (5) Merton distance to default (DD) model (Bharath & Shumway, 2008) and (6) back-propagation network model (Lippman, 1987). We assess the relative information content of these models regarding their bankruptcy prediction capability. Our tests show that dynamic logic model and DD model both provide significantly more information than the others while DD model has the highest prediction accuracy in the out of sample test. It is also worth noticing that altering coefficients and adjusting variables of the original z-score model could not significantly improve the predictive power of z-score model regarding companies in the industrial industry in the UK.


2011 ◽  
pp. 132-140
Author(s):  
B. Senthil Arasu ◽  
P. Nageswari ◽  
R. Ramya

Financial strength is a serious issue for the business firms. For measuring the financial strength of a business firm, there are lots of methods were available. But Altman’s Z-score model is one of the reliable and good methods. This model is predicting the possibilities of the bankruptcy of a business organization. The aim of the present study is analyzed the financial health of Auto Ancillary and Realty companies. For the purpose of this study, the required data collected from April 2014 to March 2018. From the study, it clearly understood that most of the sample companies are financially distressed. They better closed down their business. They are Exide industries and Amtek Auto‘s in Ancillary units and Brigade enterprises, Unitech, Prestige estate & Sunteck in Reality sector. And it also finds that Amara Raja Batteries, Omax Auto and PRICOL in Auto Ancillary units are financially healthy at present, but it will not improve their liquidity, asset productivity and solvency within 2 years it may go to bankruptcy. Phoenix Township performance sound in previous years and its performance comes down in succeeding 2 years. So it recommended to the management must take necessary steps for improving their efficiency. And also it recommends to the policymakers to make an optimum capital structure like Debt and Equity mix and proper dividend policy for maintaining sufficient earnings for future potential investment.


PERSPEKTIF ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 447-452
Author(s):  
Wardayani Wardayani ◽  
Azhar Maksum

This study is aimed to compare two methods to determine the potential for bankruptcy of the company. The method used is the Altman (Z Score) and Zavgren (Logit Analysis) models. The Z Score model is a method to predict the financial difficulties, where the score value on the Altman Z Score classifies whether a company being bankrupt or not. Zavgren developed bankruptcy prediction model with Logit Analysis which divide bankruptcy classifications. The identification problem in this research are the decline in profits occurred from the end of 2016 until 2018, and the mismatch of the increase in profits to the increase the number of assets in the Cosmetics Company, through the use of secondary data from the Indonesia Stock Exchange of companies with code MRAT, KINO, TCID, dan MBTO. Thus, the financial state of cosmetics companies listed on the Indonesia Stock Exchange (BEI) during the 2016 to2018, according to the Altman Z Score model can be categorized into 2 criteria, they are: Gray Area; MBTO and Sound Area: MRAT, KINO and TCID. Meanwhile, based on the Zavgren model, MRAT, KINO, TCID and MBTO were declared as Sound.


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