scholarly journals Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies

Nova Scientia ◽  
2021 ◽  
Vol 13 (27) ◽  
Author(s):  
Martín P. Pantoja Aguilar ◽  
Guadalupe de Montserrat Pizano Ramírez ◽  
Berenice Lerma Torres ◽  
Miguel Ángel Zavala Vargas
Keyword(s):  
Longitudinal Research ◽  
Stock Exchange ◽  
Total Error ◽  
Time Frame ◽  
Emerging Countries ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Z Scores ◽  
Score Model ◽  
High Level

Introduction: in 1968, Altman developed a multivariable predictive Z-score model to assess the probability of a public manufacturing company going to bankruptcy based on financial ratios. Later, Altman (1983) re-stated a more improved Z’’-Score model designed to apply in public or private, manufacturing, or non-manufacturing firms, but also in emerging countries. Prediction of the updated model proved to be highly efficient. This research was conducted to prove the level of accuracy of the Z’’-Score model applied to firms listed in the Mexican Stock Exchange (MSE) since there is little relevant research on this subject.                     Method: this research was conducted under a quantitative approach as a census and its scope was situational with a non-experimental and longitudinal research design. The period covered by this research was 2012-2019 since the data was available for those years under a somehow stable economic situation without significant economic ups and downs. This research considered the integration of a large financial database and the design of a typology to classify and analyze 155 firms based on a standard deviation and average results of 837 Z’’-scores. A second analysis was conducted to prove if the predicted situation (area) by the Z’’-Score corresponded to the real situation in the marketplace for every company. Results: the results showed that the accuracy level of the Altman model decreased when applied to Mexican firms. The error of the model applied to Mexican companies related to those classified in the bankruptcy prediction area was 75 % of misclassification cases. The total error of the model included all areas, or cases, was 18 % of misclassification cases. This model is supposed to be effective within a time frame of two years before a possible bankruptcy. Even considering a longer time frame, the companies located in the bankruptcy prediction area continued having misclassifications representing 57 % of error. The error for the model considering all cases and all areas, was 14 % of misclassification cases. This represented a high level of inefficiency of the model applied to an emerging country companies, such as Mexico. Discussion or conclusion: the model is certainly effective while predicting companies in the areas of non-bankrupt sector and grey, but it was inefficient when predicting the possibility of bankruptcy. It was also demonstrated that the time frame of two years is no longer effective when applying the model to Mexican companies. As a result, more research cases are needed to update the model to perform efficiently in emerging countries including country-specific conditions and considering a different time frame to predict bankruptcy.

scholarly journals TESTING BHANDARI Z-SCORE MODEL BANKRUPTCY PREDICTION USING CASH FLOW

2018 ◽  
Vol 2 (1) ◽  
pp. 121-128
Author(s):  
Barcha Handal Sakti ◽  
Ely Kartikaningdyah
Keyword(s):  
Cash Flow ◽  
Stock Exchange ◽  
Predictor Variable ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Discriminating Power ◽  
Significant Difference ◽  
Operating Cash Flow ◽  
Score Model

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.

Pengaruh Prediksi Kebangkrutan Model Altman Z-Score, Reputasi Auditor dan Opinion Shopping terhadap Opini Audit Going Concern

Owner ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 343-355
Author(s):  
Muhammad Yunus ◽  
Calen Calen ◽  
Sarida Sirait
Keyword(s):  
Stock Exchange ◽  
Sampling Technique ◽  
Bankruptcy Prediction ◽  
Manufacturing Companies ◽  
Z Score ◽  
Audit Opinion ◽  
Going Concern ◽  
Opinion Shopping ◽  
Score Model ◽  
Auditor Reputation

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.

scholarly journals BANKRUPTCY PREDICTION OF THE COMPANY USING ALTMAN Z–SCORE METHOD FOR THE CONVENTIONAL BANKS REGISTERED IN THE INDONESIA STOCKS EXCHANGE (BEI)

2017 ◽  
Vol 2 (02) ◽  
pp. 11
Author(s):  
Irwansyah .
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Gray Area ◽  
Analysis Technique ◽  
Score Analysis ◽  
Score Method ◽  
Score Model ◽  
Conventional Banks

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.

scholarly journals Company Bankruptcy Prediction Coal Mining Sector Listed on the Indonesia Stock Exchange and Its Impact on Stock Prices

2021 ◽  
Vol 3 (3) ◽  
pp. 95-106
Author(s):  
Erik Priambodo ◽  
Augustina Kurniasih
Keyword(s):  
Coal Mining ◽  
Stock Prices ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Mining Sector ◽  
Mining Companies ◽  
Panel Data Regression ◽  
Data Regression ◽  
Score Model

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.

scholarly journals Analisis Potensi Kebangkrutan: Perbandingan Model Altman dengan Zavgren

PERSPEKTIF ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 447-452
Author(s):  
Wardayani Wardayani ◽  
Azhar Maksum
Keyword(s):  
Stock Exchange ◽  
Secondary Data ◽  
Identification Problem ◽  
Bankruptcy Prediction ◽  
Logit Analysis ◽  
Z Score ◽  
Gray Area ◽  
Financial Difficulties ◽  
Score Model ◽  
Analysis Models

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.

FINANCIAL DISTRESS PREDICTION AND SEEING THE INFLUENCE OF THE ALTMAN RATIO ON COMPANY FINANCIAL DISTRESS

2018 ◽  
Vol 23 (3) ◽  
pp. 236-243
Author(s):  
Hadhi Dharmaputra Juliyan ◽  
Bertilia Lina Kusrina
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Large Role ◽  
Corporate Bankruptcy ◽  
Mining Companies ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Score Model

This research aims to determine the level of the bankruptcy of the company and to see if the Altman ratio can predict the condition of corporate bankruptcy in mining companies on the Indonesia Stock Exchange because mining companies have a large role in the Indonesian economy. This study uses the Altman Z-Score model analysis to see how much the company's bankruptcy prediction and uses logistic regression to see how much the influence of the Altman ratio in predicting corporate bankruptcy. Keywords: financial distress, the Altman z–score, bankruptcy prediction

ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z- SCORE DAN ZMIJEWSKI PADA PERUSAHAAN KOSMETIK YANG TERDAFTAR DI BURSA EFEK INDONESIA

2020 ◽  
Vol 5 (1) ◽  
pp. 24-33
Author(s):  
Dewi Oktary
Keyword(s):  
Quantitative Data ◽  
Stock Exchange ◽  
Secondary Data ◽  
Bankruptcy Prediction ◽  
The Other ◽  
Z Score ◽  
Gray Area ◽  
Score Method ◽  
Data Source ◽  
Score Model

Increasingly intense competition in the cosmetics industry in Indonesia, one of which is the number of artists opening a cosmetics business and besides the entry of many cosmetics brands from abroad which makes existing cosmetic companies must be careful in running their business. This study aims to predict the bankruptcy of cosmetics companies listed on the Indonesia Stock Exchange with the Altman Z-Score model and the Zmijewski model. The sample in this study was cosmetic companies listed on the Main Board of the Indonesia Stock Exchange as many as 4 companies. The data source used is secondary data taking data from the IDX, the type of data used is quantitative data. The result of this research is bankruptcy prediction using the Altman-Z Score method showing that PT. Martino Berto, Tbk for 2016 is included in the Gray Area category while in 2017-2018 it is predicted to go bankrupt while for PT. Mustika Ratu, in 2016 - 2018 entered the Gray Area category while the other two companies namely PT. Mandom Indonesia, Tbk and PT. Unilever, Tbk from 2016 to 2018 is predicted not to go bankrupt. Meanwhile, using the Zmijewski method in cosmetics companies listed on the Indonesia Stock Exchange in the period 2016-2018 is predicted not to go bankrupt. From the comparison between the Altman Z-Score model and the Zmijewski model, the Zmijewski model has an effectiveness of 100% compared to the Altman Z-Score model which has an effectiveness level of 50%.

scholarly journals ANALISIS TINGKAT AKURASI MODEL ALTMAN Z-SCORE, INDEKS KEPAILITAN, DAN INDEKS IN05 SEBAGAI PREDIKTOR KEBANGKRUTAN PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2011-2015

Jurnal Ecogen ◽  
2018 ◽  
Vol 1 (4) ◽  
pp. 197
Author(s):  
Diana Novita
Keyword(s):  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Total Sample ◽  
Bankruptcy Prediction ◽  
Manufacturing Companies ◽  
Z Score ◽  
Sample Test ◽  
Score Model ◽  
Post Hoc

This study discusses the use of bankruptcy prediction model that does not exist applied in Indonesia and determine the accuracy of each model. The research objective is to analyze the differences in outcome prediction and know the model that has the best accuracy level between the model Altman Z-Score, Bankruptcy Index, and IN05 Index. This type of research is a comparative study, the population of all manufacturing companies listed on the Indonesia Stock Exchange in 2011 to 2015. The sample is determined by purposive sampling method so acquired 28 companies, and the total sample is 140 years old company. Data used is secondary data obtained from the official website of Indonesia Stock Exchange (www.idx.co.id). The analytical method used is the analysis of different test-independent k-sample test, descriptive statistics and the accuracy of the model using post hoc test and the type of error. The results show that: 1) there are significant differences between the model of the Altman Z-Score model Insolvency Index, and models IN05 index on manufacturing companies listed on the Stock Exchange. 2) The model has the best accuracy by post hoc test is a model of the Altman Z-Score and by type of error is the most accurate models are models IN05 index.Keywords: Altman Z-Score, Insolvency Index, IN05, Bankruptcy

scholarly journals ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z-SOCRE DAN MODEL INTERNAL GROWTH RATE

2018 ◽  
Vol 1 (1) ◽  
pp. 18-25
Author(s):  
Dian Safitri ◽  
Dina Fitri Septarini
Keyword(s):  
Growth Rate ◽  
Empirical Study ◽  
Stock Exchange ◽  
Secondary Data ◽  
Analytical Techniques ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Rate Model ◽  
Research Objects ◽  
Score Model

Analysis of Bankruptcy Prediction Using Altman Z-Score Model and Internal Growth Rate Model An Empirical Study on Delisting Companies from Indonesia Stock Exchange Year 2012-2015. This study aims to predict bankruptcy using the Altman Z Score model and the Internal Growth Rate model in delisting companies from the Indonesia Stock Exchange in 2012-2015 and to find the most appropriate model in predicting bankruptcy.The number of companies studied were 12 companies delisted from the Indonesia Stock Exchange 2012-2015 with a year of observation for 3 years before delisting, so that the object of research selected as many as 36 objects of research, with the object that can be studied as many as 24 research objects. The data used is secondary data. Analytical techniques used are Altman Z-Score model and Internal Growth Rate model.Results from 24 objects of the research using modification Altman Z-Score model there are 10 objects that fall into the category of bankruptcy. While using the Internal Growth Rate model there are 12 companies that fall into the category of bankruptcy. From the results of the analysis can be seen that the model of Internal Growth Rate is more appropriate and easier to use to shave bankruptcy of 12 companies delisting from the Indonesia Stock Exchange.   Keywords: Altman Z-Score, Internal Growth Rate, and Prediction of bankruptcy.

scholarly journals Stock Prices Predicted by Bankruptcy Condition?

2018 ◽  
Vol 9 (2) ◽  
pp. 105-114
Author(s):  
Irawati Junaeni
Keyword(s):  
Stock Prices ◽  
Financial Distress ◽  
Stock Price ◽  
Sampling Method ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Analysis Method ◽  
Simple Regression Analysis ◽  
Score Model

This research had two objectives. First, it determined the prediction of the method of Altman Z-Score whether it could classify banking positions, bankruptcy, or financial distress in the go-public bank in Indonesia Stock Exchange. Second, it was to know the influence of value position of Altman Z-Score on the stock price. The population was 84 banking company listed on the Indonesia Stock Exchange in 2010-2015. The sampling method was purposive sampling. Moreover, data analysis method used was a simple regression analysis. For data processing, it used software Eviews 8. The Z-Score calculations predict the potential bankruptcy of go-public bank in 2010-2015. All results show that Z-Score has the small score of 1,81. It can be said there is a potential bankruptcy. For t-test, it can be concluded that Z-Score has the positive and significant effect on the stock price. The ability of Z-Score values in explaining the stock price is 95,50% while the remaining 4,50% is influenced by other variables that are not analyzed in the research. With some weaknesses of Altman’s Z-Score model, this research has the implication for management bank. It improves the financial performance for the future to avoid opportunity bankruptcy prediction. The results show how the effect of bankruptcy on banking stock prices.

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