scholarly journals ANALISIS FINANCIAL DISTRESS SAAT KRISIS KEUANGAN GLOBAL: STUDI EMPIRIS PADA BUMN NON-KEUANGAN

2021 ◽  
Vol 2 (2) ◽  
pp. 107-124
Author(s):  
Tiffany Mica Nakamura
Keyword(s):  
Financial Distress ◽  
Prediction Models ◽  
Stock Exchange ◽  
Secondary Data ◽  
Comparative Test ◽  
Annual Reports ◽  
Z Score ◽  
Accuracy Test ◽  
Accuracy Level ◽  
Data Analysis Methods

This study aims to determine the differences and levels of accuracyof the Altman Z-Score, Springate S-Score, and Zmijewski X-Score inpredicting financial distress before, during, and after the global financialcrisis. The sample in this study used nine state-owned companies in thenon-financial sector, which were listed on the Indonesia Stock Exchange forthe period 2005–2012. Data collection used secondary data from thecompany’s annual reports—data analysis methods using the Kruskall - Wallistest as a comparative test used to determine differences. This study indicatesno differences in predictions before, during, and after the global financialcrisis. The accuracy test states that the three prediction models are appropriate,but the Altman Z-Score is the model with the highest accuracy level.

Measuring financial distress of non-bank financial institutions of Bangladesh using Altman’s Z-Score model

2020 ◽  
Vol 13 ◽  
pp. 15-28
Author(s):  
Mohammad Rifat Rahman ◽  
Md. Mufidur Rahman ◽  
Athkia Subat
Keyword(s):  
Financial Institutions ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Vital Role ◽  
Annual Reports ◽  
Z Score ◽  
Factors Affecting ◽  
Financial Soundness ◽  
The Government

Non-bank financial institutions (NBFIs) are recognized as the fundamental of a financial market as they complement the banking institutions. Since 1981, NBFIs have been playing a vital role in the economic growth of Bangladesh. Unfortunately, in the recent years most of the NBFIs have been found financially distressed. However, few NBFIs that were included in our sample claimed themselves as potential companies with sound financial performance though it was highly criticized. Therefore, the motivation for conducting this study is to examine the financial soundness of selected NBFIs using Altman’s Z score (1995). This study involved 20 NBFIs out of 23 Dhaka Stock Exchange (DSE) listed institutions, which were selected based on information availability by considering A, B and Z categories from 2014 to 2018 period. The secondary data were collected from the annual reports of the selected companies over the period. The findings are as follows: 95% of the 20 NBFIs were in distress zone during the study period and only 5% NBFIs were in safe zone during 2017-2018 period. Therefore, the analysis predicted that within the upcoming years a few of the NBFIs will be approaching bankruptcy. Finally, it is suggested that the government, respective regulatory authority, and policy makers to pay an immediate attention on mitigating the factors affecting the financial distress.

The Effect of Bankruptcy Possibility on Audit Delay and Timeliness (Empirical Study on Manufacturing Companies Listed in Indonesian Stock Exchange in the Period of 2012-2016)

2019 ◽  
Vol 2 (2) ◽  
pp. 118-146
Author(s):  
Triana Meinarsih ◽  
Abdul Yusuf ◽  
Muhammad Zilal Hamzah
Keyword(s):  
Quantitative Research ◽  
Stock Exchange ◽  
Secondary Data ◽  
Annual Reports ◽  
Manufacturing Companies ◽  
Z Score ◽  
Quality Of Accounting Information ◽  
Independent Variable ◽  
A Company

Audit delay and timeliness are important factors that influence the quality of accounting information in term of relevance. This study provides empirical evidence to answer the question of how bankruptcy possibility impacts on audit delay and timeliness.  This research studies manufacturing firms listed in Indonesian Stock Exchange (IDX) in the period of 2012-2016. Data are taken from official website of IDX. This study is a quantitative research that seek to find out relationship between independent variable and dependent variable. External secondary data used are annual reports accessed from IDX website. Measurement used is Z-Score Altman model prediction, while simple linear regression is employed as technical analysis. This study finds that bankruptcy possibility which is measured by ZScore is negatively influence audit delay and timeliness. Any decrease of Z-Score shows the possibility of a company experience bankruptcy and therefore causes audit delay and timeliness.

scholarly journals Pengaruh Likuiditas, Leverage, Profitabilitas, dan Ukuran Perusahaan terhadap Financial Distress di Sektor Trade, Service, and Invesment

2021 ◽  
Vol 9 (3) ◽  
pp. 1227-1240
Author(s):  
Hasivatus Sariroh
Keyword(s):  
Firm Size ◽  
Financial Distress ◽  
Ordinal Data ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Annual Reports ◽  
Return On Assets ◽  
Current Ratio ◽  
Independent Variables

This study is a quantitative study that aims to determine the effect of the current ratio, debt to asset ratio, return on assets, and firm size on financial distress. Logistic regression method was used to test all relationships between independent variables and dependent variables with nominal/ordinal data scales. The dependent variable in this study is financial distress. The independent variables in this study are liquidity, leverage, profitability and firm size. This study uses secondary data from annual reports of trading, service, and investment companies listed on the Indonesia Stock Exchange from 2016 to 2018. The population used is companies in the trade, services, and investment sectors listed on the Indonesia Stock Exchange (IDX). from 2016 to 2018 with a total of 162 companies selected using purposive sampling technique. The results of hypothesis testing indicate that the current ratio, debt to asset ratio, return on assets, and firm size have no effect on the company's financial distress. From research conducted by researchers, for management to be used as a basis to take corrective actions if there are indications that the company experiencing financial distress. For investors, to be used as a basis in making the right decision to invest in a company.

scholarly journals ASOSIASI KARAKTERISTIK CEO TERHADAP POTENSI KESULITAN KEUANGAN PERUSAHAAN

2020 ◽  
Vol 1 (2) ◽  
pp. 153-168
Author(s):  
Felix Leonardo Tanjaya ◽  
Eko Budi Santoso
Keyword(s):  
Financial Distress ◽  
Work Experience ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Total Sample ◽  
Annual Reports ◽  
Company Performance ◽  
Data Types ◽  
Facial Masculinity

This study aims to determine the effect of CEO characteristics interms of facial masculinity, education, and experience to potential of financialdistress. Facial masculinity was measured using dummy variables consistingof masculinity and feminism. Education was measured using dummyvariables of educational level; meanwhile, experience was measured usingdummy variables from CEO work experience. This research used quantitativewith secondary data types taken from annual reports of non-financialcompanies that are listed on Indonesia Stock Exchange. The sampling methodused purposive sampling with the observation period of 2016–2018 andobtained a total sample of 259 samples. The method data analysis usedmultiple linear regression analysis. The result showed that: (1) CEO facemasculinity did not affect financial distress, (2) CEO education did notaffect financial distress, (3) CEO experience positively influenced financialdistress. The results showed the fact that CEO experience is an importantfactor that could improved company performance for avoiding financialdistress potential.

scholarly journals ANALISIS PENILAIAN FINANCIAL DISTRESS MENGGUNAKAN MODEL ALTMAN (Z-SCORE) PADA PERUSAHAAN FARMASI YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2013-2015

2017 ◽  
Vol 5 (1) ◽  
pp. 55
Author(s):  
Sri Yati ◽  
Katarina Intan Afni Patunrui
Keyword(s):  
Financial Distress ◽  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Pharmaceutical Companies ◽  
Z Score ◽  
Financial Reports ◽  
Book Value ◽  
Total Debt ◽  
Score Model

This study aims to observe the financial distress assessment for pharmaceutical companies listed on the Indonesia Stock Exchange using the Altman Z-Score model. The sample is selected using purposive sampling method. Ten pharmaceutical companies were selected with the criteria listed in the Indonesia Stock Exchange (BEI) and regularly published financial reports in 2013 until 2015. Secondary data was derived from www.idx.co.id site.  The results indicate that the Altman Z-Score model can be implemented in detecting the possibility of financial distress in the pharmaceutical company. Working capital to total assets and book value equity to book value of total debt are two determinant variables which is determining the decrease in Z-score value in this research.  One from ten companies have the lowest value of the Z-Score and experiencing financial distress. For two years, the company is in distress zones but in the third year, the company is managed to increase the value of the company and included in the gray zones. This company must continue to strive in order to stabilize the company's financial and asset utilization to obtain maximum profit, and until it was declared as a healthy company.

scholarly journals Analysis of Accuracy Level of Altman Z-Score Model and Springate Model in Measuring the Potential of Financial Distress in Plantations Industries

2019 ◽  
pp. 16-25
Keyword(s):  
Financial Performance ◽  
Financial Distress ◽  
Secondary Data ◽  
Financial Data ◽  
Z Score ◽  
Financial Difficulties ◽  
Accuracy Level ◽  
Score Model

This study aimed to analyze the level of bankruptcy using Altman Z-Score model of modifications and models Springate, the Plantations Company period 2014-2017. The data used in this research is secondary data, financial data Plantations Company taken from the site www.idx.co.id. Based on the results of this study show that the model of the Altman Z-Score modification Plantations Industries was having financial difficulties which would be potentially bankrupt, it can be seen from the Z-Score of less than 1.1 in the period 2014-2017 and no different from using a model that generates value Springate S-Score <0.862 means that the financial performance Plantations company are experiencing financial difficulties during the 2014-2017 period and potentially going bankrupt.

Impact of Good Corporate Governance on Financial Distress in the Consumer Goods Sector Company

2017 ◽  
Vol 2 (4) ◽  
pp. 46-55
Author(s):  
Sri Marti Pramudena
Keyword(s):  
Corporate Governance ◽  
Consumer Goods ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Institutional Ownership ◽  
Annual Reports ◽  
Manufacturing Companies ◽  
Good Corporate Governance ◽  
A Company

Objective - Financial distress is referred to as a condition in which a company's operations result in insufficient funds to meet its obligations (insolvency). The success or failure of a company greatly depends on the corporate governance of the company. This study aims to identify the relationship between the existence of good corporate governance and the probability of financial distress. Methodology/Technique - This study used secondary data obtained from annual reports from 2009 to 2014. The data is gathered from consumer goods manufacturing companies, that are listed on the Indonesian Stock Exchange (BEI). The sample includes 10 companies. The method of analysis used is multiple linear regressions. Findings - The results of the study show that institutional ownership and managerial ownership adversely affect the possibility of financial distress. On the other hand, the proportion of commissioners and the number of board of directors have a positive effect on the probability of financial distress. Novelty - This study found that institutional ownership (IO) has an inverse effect on the financial distress of a company. Type of Paper - Empirical Keywords: Good Corporate Governance; Financial Distress; Corporate Performance. JEL Classification: G30, G34, G39.

scholarly journals ANALYSIS OF THE FACTORS THAT AFFECT THE COMPANY'S ACCOUNTING CONSERVATISM

2020 ◽  
Vol 5 (2) ◽  
pp. 101
Author(s):  
Wulan Wahyuni Rossa Putri ◽  
Nilda Tartilla ◽  
M. Nofal Pamungkas
Keyword(s):  
Real Estate ◽  
Financial Reporting ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Capital Intensity ◽  
Accounting Conservatism ◽  
Annual Reports ◽  
Construction Sector ◽  
Manufacturing Companies

Accounting conservatism is a precautionary principle in financial reporting. In this principle, it slows down the recognition of revenue and accelerates the recognition of costs so as to result in lower profits and assets, as well as high costs and debt. This study aims to determine the factors that affect accounting conservatism in the Property Real Estate and Buliding Construction sector manufacturing companies listed on the IDX.The data source used in this research is secondary data. Data is sourced from audited annual reports obtained from the IDX official website, namely www.idx.co.id. The population of this research is manufacturing companies listed on the Indonesia Stock Exchange, with research samples in the Property Real Estate and Buliding Construction sector in the 2013-2017 period. The samples were determined using purposive sampling method. The method of analysis used in this research is multiple regression with the SPSS version 25 program and hypothesis testing is done using multiple linear regression method.The results of this study indicate that leverage has no effect on accounting conservatism with a significance value of 0.554. Financial distress has no effect on accounting conservatism with a value of 0.852. Meanwhile, capital intensity has an effect on accounting conservatism with a significance value of 0.000. As well as Leverage, Financial Distress, and Capital Intensity simultaneously affect accounting conservatism.

scholarly journals ANALISIS PREDIKSI TINGKAT KEBANGKRUTAN DENGAN METODE ALTMAN Z-SCORE DAN ZMIJEWSKI PADA PT BAKRIE TELECOM TBK PERIODE 2015-2017

2019 ◽  
Vol 3 (01) ◽  
Author(s):  
Suci Ariyani ◽  
Djumali Djumali ◽  
Ida Aryati
Keyword(s):  
Data Analysis ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Z Score ◽  
Analysis Model ◽  
Analysis Techniques ◽  
Financial Condition ◽  
Grey Area ◽  
Telecommunication Companies

The purpose of this research is to know financial condition of Bakrie Telecom Tbk company using Altman and Zmijewski's analysis model period 2015-2017, during the period so its be able to predict financial distress happened inside the company. The data used to this research is secondary data, with population telecommunication companies go public enrolled in the Indonesia Stock Exchange (BEI) period 2015-2017. Data analysis techniques that used is Altman and Zmijewski's dicriminant analysis. The Altman's analysis model classified into three company categories, which are company that is in broken condition, grey area and not bankrupt/healthy. The Zmijewski's analysis model classified into two company categories, which are potentially bankrupt company and unpotentially bankrupt company/health. The results of the Bakrie Telecom Tbk company's financial distress analysis period of 2015-2017 used the Altman's model showed that company was not in bankrupt category/health .The results of the Zmijewski's analysis model showed in 2015 was not in bankrupt category/health category and in the year 2016-2017 was in the bankrupt category. Keywords: Bankruptcy , Altman , Zmijewski

scholarly journals Akurasi Model Logistik Springate, Zmijewski, dan Grover Dalam Menakar Kesulitan Keuangan Perusahaan Pembiayaan

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Munawarah Munawarah
Keyword(s):  
Logistic Regression ◽  
Predictive Models ◽  
Financial Distress ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Total Sample ◽  
Annual Reports ◽  
Analysis Model ◽  
Purposive Sampling

This study aims to determine springate, grover and zmijewski able to predict the condition of financial distress in finance companies listed on the Indonesia Stock Exchange. From  three models can be known which model is the most accurate in predicting financial distress. There are 17 companies in Financing sector as population in this study from 2013-2017. Using purposive sampling technique, total sample of 85 financing companies was obtained. Secondary data were used in this research sourced from the company's annual reports. The analysis model used is logistic regression. Simultaneously, all predictive models affect the probability of financial distress. While partially only Zmijewski can influence the prediction of financial distress conditions in Financing sub-sector companies listed on the Indonesia Stock Exchange. Nagelkerqe Square value shows 0.606 meaning that only 60.6% variation of the accuracy of these three models in predicting financial distress conditions of finance companies. While 39.4% can be explained by other models not examined in this study.

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