Business Bankruptcy Prediction Models: A Significant Study of the Altman’s Z-Score Model

2012 ◽  
Author(s):  
Sanobar Anjum Siddiqui
Keyword(s):  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Score Model

scholarly journals Bankruptcy prediction models for large agribusiness companies in AP Vojvodina

2021 ◽  
Vol 68 (3) ◽  
pp. 805-822
Author(s):  
Dragan Milić ◽  
Dragana Tekić ◽  
Vladislav Zekić ◽  
Tihomir Novaković ◽  
Milana Popov ◽  
...  
Keyword(s):  
Financial Stability ◽  
Agricultural Sector ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Food Sector ◽  
Bankruptcy Risk ◽  
Quick Test ◽  
Score Model

The aim of this paper is to present application of different methods used for predicting bankruptcy of large agricultural and food companies in AP Vojvodina, as well as to determine which model is the most suitable for analyzing the companies from the observed sectors. The following three models were applied in the paper: Altman's Z'-score model, Kralicek DF indicators and Kralicek Quick test. The analysis included five companies from the agricultural sector and five companies from the food sector operating on the territory of AP Vojvodina in the period from 2015 to 2019. The results of the research based on the applied models showed that different conclusions can be made about the financial stability of the observed companies. Altman's Z'-score model provided the most rigorous forecast in terms of the bankruptcy risk, while the results of Kralicek DF indicators and Quick test are relatively similar.

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 Industrial Industry in the UK

2017 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Wong Ming Nok
Keyword(s):  
Back Propagation ◽  
Dynamic Logic ◽  
Bankruptcy Prediction ◽  
Logic Model ◽  
Z Score ◽  
Out Of Sample ◽  
Sample Test ◽  
Score Model ◽  
The Uk ◽  
Propagation Network

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.

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 PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z-SCORE PADA PERUSAHAAN RITEL YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2014-2018

2021 ◽  
Vol 9 (1) ◽  
pp. 84
Author(s):  
Rosmayana Rusman
Keyword(s):  
Sampling Technique ◽  
Financial Statements ◽  
Critical Issue ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Financial Condition ◽  
Dangerous Zone ◽  
Score Model ◽  
Retail Organizations ◽  
High Degree

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

scholarly journals Bankruptcy Prediction of Industrial Industry in the UK

2017 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Wong Ming Nok
Keyword(s):  
Back Propagation ◽  
Dynamic Logic ◽  
Bankruptcy Prediction ◽  
Logic Model ◽  
Z Score ◽  
Out Of Sample ◽  
Sample Test ◽  
Score Model ◽  
The Uk ◽  
Propagation Network

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.

scholarly journals Does The Development Context Affect Bankruptcy Prediction Models’ General Accuracy? A Comparative Analysis Of Four Multivariate Discriminant Models In The Italian Context

2016 ◽  
Vol 12 (10) ◽  
pp. 445 ◽  
Author(s):  
Salvatore Madonna ◽  
Greta Cestari ◽  
Francesca Callegari
Keyword(s):  
Prediction Models ◽  
Predictive Accuracy ◽  
Bankruptcy Prediction ◽  
Development Context ◽  
Wide Scale ◽  
Discriminant Models ◽  
Score Model ◽  
The One ◽  
Italian Context ◽  
Multivariate Discriminant

This research starts from the work by Madonna and Cestari (2015) that aimed at assessing the usability of three bankruptcy prediction models applied in contexts other than the ones of their elaboration, in order to evaluate their generalizability and the possibility to apply them in wide-scale investigations. We took the cue from that study to assess the usability of four bankruptcy prediction models, when applied to a sample with characteristics other than the ones related to their elaboration. We aimed at verifying the predictive accuracy and the discriminant capacity of the four models, basing on the assumption that the performances displayed by bankruptcy prediction models are usually better when they are applied in contexts similar to the one of their elaboration. Given this premise, we hypothesized that Italian models should perform better than the American one. In order to verify this hypothesis, we tested the four multivariate discriminant models twice: the predictive accuracy was tested applying the models on a sample of firms gone bankrupt within 2012 and 2014; the discriminant capacity on a sample equally composed by bankrupt and operating firms. Both samples were composed by firms located in Italy and operating in recent years. Hence the sample provided and the context of application were different from the ones of the models‘ elaboration. The results show that even if the Italian models were elaborated basing on contexts more similar to the one of the present application, the best performance is reached by the American Altman’s Z‘-Score model.

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