scholarly journals Bankruptcy Prediction using Multivariate Discriminant Analysis - Empirical Evidence from Cases Referred to NCLT

2019 ◽  
Vol 8 (9) ◽  
pp. 13-17
Keyword(s):  
Bankruptcy Prediction ◽  
Company Law ◽  
Annual Reports ◽  
Empirical Literature ◽  
Z Score ◽  
The Subject ◽  
Bankruptcy Code ◽  
Score Model ◽  
Insolvency Proceedings ◽  
Multivariate Discriminant

The study is about bankruptcy prediction using multivariate model of analysis for the case of twelve large accounts which were referred to National Company Law Tribunal for insolvency proceedings. Corporate failures affect all stakeholders. It’s also a fact that companies are never shielded from bankruptcy. With the mounting of India’s non-performing assets, the pronouncement of Insolvency and Bankruptcy Code is a strong suit for maximising value of lenders as well as borrowers. The first part of the paper throws light on the code, the progress made and challenges faced. On the empirical literature side, the paper applies the famous Altman’s Z-Score model on the first twelve companies on which insolvency proceedings are on. Suitability of the model is supported by literature review on the subject. Financial data gathered from Annual reports are analysed to arrive at Z-Score results. The strength of the results are statistically examined through hypotheses tested using regression and feasibility of the model is tested using ANOVA. The paper presents the limitation of the study, a discussion of the suitability of the model and further scope of research in the area

scholarly journals Validity of Altman Z-Score Model to Predict Financial Failure: Evidence From Jordan

2018 ◽  
Vol 10 (8) ◽  
pp. 181 ◽  
Author(s):  
Sufian Al-Manaseer ◽  
Suleiman Al-Oshaibat
Keyword(s):  
Stock Exchange ◽  
Financial Statement ◽  
Insurance Companies ◽  
Z Score ◽  
Financial Reports ◽  
Financial Failure ◽  
Amman Stock Exchange ◽  
The Face ◽  
The Subject ◽  
Score Model

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.

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 Financial Soundness of Cement Industry of Bangladesh: An Empirical Investigation Using Z-score

2014 ◽  
Vol 1 (1) ◽  
pp. 16-22 ◽  
Author(s):  
A. N. K. Mizan ◽  
Md. Mahabbat Hossain
Keyword(s):  
Empirical Investigation ◽  
Raw Materials ◽  
Cement Industry ◽  
Annual Reports ◽  
Business Firm ◽  
Financial Health ◽  
Z Score ◽  
Financial Soundness ◽  
Financial Decision ◽  
Score Model

For measuring the financial health of a business firm, there are lots of techniques available. But the Altman’s Z-score has been proven to be a reliable tool across contexts. Bangladesh cement industry is a unique one because, the industry is producing a higher amount of cement than the local demand having no supply of local raw materials. The main objective of the study is to assess the fundamental financial health of this industry using Z-score model. All listed cement firms are considered in this study. The required information has been collected from the annual reports of the selected companies and from other sources. The study revealed that two firms, Heidelberg cement and Confidence Cement, are financially sound whereas other three are not in a good position. The findings of the study can be useful for the managers to take financial decision, the stockholders to choose investment options and others to look after their interest in the concern cement manufacturers of the country.

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.

Sign in / Sign up

Export Citation Format

Share Document