Analysis Of Financial Distress Research Articles

Gauging Bankruptcy using Altman’s Z-Score Empirical Investigation from the Pharmaceutical Sector

This study aims to construct timely responses to escape financial distress and further losses and prevent financial crises. The main focus of the research is to present the analysis of financial distress on the performance of the five firms listed on the Pakistan Stock Exchange under the Pharmaceutical sector within ten years. If financial distress is not identified in time and inappropriate measures are taken, insolvency (bankruptcy) is likely to occur. This study sought to test the validity of Altman’s Z-score and its effectiveness in identifying the financial distress on the performance of firms in the pharmaceutical sector. The sample size consists of cross-sectional time series annual data of five pharmaceutical companies listed on the Pakistan Stock Exchange (PSX). The data set has been tracked for ten years, from 2006 to 2016. The analytical model (Z-score) developed by Edward Altman is used in this study as the statistical technique. The results concluded that Abbot, Glaxo and Wyeth generally experienced stability and incline in the Z-Score values throughout the years. These companies have been fit into non-financial distress. On the other hand, Ferozsons and Highnoon have been in between a range of grey areas. The companies had a probability of experiencing the problems of financial distress. Consequently, companies have started to reach their peak and fit into non-financial distress.

Analysis of Financial Distress in Construction Companies with the Altman Method

Analysis of Financial Distress in Construction Companies with the Altman Method

Analysis of Financial Distress in Construction Companies with the Altman Method

Analysis of Financial Distress in Construction Companies with the Altman Method

Analysis of Financial Distress in Construction Companies with the Altman Method

The Construction sector is one of the most affected by Covid-19, many companies are found to be bankrupt. This study used regression panel data with more than 30 observations. The variables analyzed are current ratio, DAR, ROA and sales growth. The results of the current ratio research have a positive effect with a significant coefficient of 1.292 on financial distrees proxied with the Z-Score, meaning that the higher the liquidity value will be followed by the Z-score value so that financial difficulties are lower (negative). DAR has a positive effect on the value of the coefficient of 1.142 greater than 0.05 so that it is not significant or influential on financial difficulties proxied through the Z-Score, meaning that the size of leverage cannot be used as a reference to assess the financial difficulties experienced by the company. ROA has a positive effect with a coefficient of 5.377 and affects financial difficulties proxied through the Z-Score, meaning that the high profitability value will be followed by a high Z-score value so that financial difficulties will be lower (negative effect). Sales growth has a negative effect with a coefficient of -0.834 has no effect on financial difficulties proxied through the Z-Score, meaning that the size of sales growth cannot be used as a reference to assess the financial difficulties experienced by the company.

Financial Distress Analysis Using Altman Z-Score, Springate and Zmijewski in Retail Companies on the IDX

Islamic Social Reporting (ISR) is an index of social accountability disclosure whose indicators refer to Islamic ethical principles. Islamic banking operates by sharia principles. Therefore the disclosure of ISR in Islamic banking must be within the corridors of Islamic theology. This study uses the E-Views software to identify the factors that influence the level of exposure to Islamic Social Reporting (ISR) in Islamic banking in Indonesia. The factors examined in this study are company performance and company size towards Islamic Social Reporting. The results of this study show that financial performance proxied by ROA has no effect on ISR with a calculated T value of 1.338357, and financial performance proxied by NPF has no impact on Islamic Social Reporting with an estimated T value of 1.405019. Company size is a proxy for the Size that affects Islamic Social Reporting, with a T-test result of 3.077773 <2.03693. The results of the F test obtained a value of 0.021230 <0.05, which means that the variables NPF, ROA, and Size together influence the Islamic Social Reporting of Islamic Banks in Indonesia for the 2016-2020 period.

Financial Distress Analysis of Textile and Garment Companies Listed on the Indonesian Stock Exchange

Results study this shows that several company textiles And garments are listed on the IDX with sound performance and bad. No, there is a company with good performance finance. A company that owns performance fewer finances Good in the category vulnerable is Sunson Textile Manufacture Tbk And Trisula International Tbk. This company, on average, on the position of Gray Area (prone) or is in between the range of 1.81 to 2.99. A company that owns bad performance finances (bankruptcy) or experience difficulty financially (financial distress) are PT Panasia Indo resources Tbk, Asia Pacific Investama Tbk, Ricky Putra Globalindo Tbk, and Star Petrochem Tbk. This company's average value is under 1.81, which is limited from the category performing company finance badly (broke). Furthermore, researchers can add or compare the author's analysis model use with other analytical models related to the method Altman Z-Score so that they can analyze giving problems results And input to the company.

Analysis of Financial Distress and Financial Performance Before and After the Covid-19 Pandemic

Analysis of Financial Distress and Financial Performance Before and After the Covid-19 Pandemic

Financial Distress Analysis Using the Ohlson Model in Indonesian State Owned Enterprises

This study aims to analyze financial distress conditions using the Ohlson financial distress model in SOEs Non-Financial Sector for the 2017-2020 financial year performance period. The object of analysis is non-financial and banking SOEs registered under Ministry of SOEs. The results of the study are: 1) The aggregate probability of default for all SOEs has increased from 2017 to 2020; 2) the highest increase is the Probability of Default in 2020 compared to the Probability of Default in 2019; 3) SOEs in the Tourism Sector are the sectors that experience the most financial distress in 2020, while the Plantation and Forestry sector are the least financial distress in 2020; 4) SOEs in the same sector may show a different trend of increasing/decreasing Probability of Default.

To Recognize Indication of Financial Distress and Or Bankruptcy of Five Textile Company for Five Years Period Using Five Financial Distress Models

Background: In a business, risk of profit and loss is an inevitability. Every company have their own ways to mitigate those risk, prepare a proper treatment, and other efforts get the predetermined purpose, that is profit. Serious risk and its consequences can bring company into financial distress, and in the next step can become bankrupt. The Indications of it can be seen from the financial performance of the companies. Aim: To find out whether a company engaged in the textile and textile products sector is in serious financial difficulty which could have implications for bankruptcy, several theories have been developed. This study is to analyze indication of financial distress and its possibility to become bankrupt. The study is using financial data of five textile and textile product companies listed on the Indonesia Stock Exchange for five years of 2017 – 2021, using five models of Analysis of Financial Distress, that are Zmijewski Model, Fulmer Model, Grover Model, Altman Z-Score Model, and Springate Model. Method: This study uses secondary data on the textile companies listed on the Indonesia Stock Exchange. The sample used in this study were five companies. The sample selection uses purposive sampling. This type of research used in this research is quantitative descriptive, namely research on problems in the form of the current facts of a population. Testing research data using data analysis of model financial distress. Findings: This study uses secondary data on the textile companies listed on the Indonesia Stock Exchange. The sample used in this study were five companies. The sample selection uses purposive sampling. This type of research used in this research is quantitative descriptive, namely research on problems in the form of the current facts of a population. Testing research data using data analysis of model financial distress.

To Recognize Indication of Financial Distress and Or Bankruptcy of Five Textile Company for Five Years Period Using Five Financial Distress Models

Background: In a business, risk of profit and loss is an inevitability. Every company have their own ways to mitigate those risk, prepare a proper treatment, and other efforts get the predetermined purpose, that is profit. Serious risk and its consequences can bring company into financial distress, and in the next step can become bankrupt. The Indications of it can be seen from the financial performance of the companies. Aim: To find out whether a company engaged in the textile and textile products sector is in serious financial difficulty which could have implications for bankruptcy, several theories have been developed. This study is to analyze indication of financial distress and its possibility to become bankrupt. The study is using financial data of five textile and textile product companies listed on the Indonesia Stock Exchange for five years of 2017 – 2021, using five models of Analysis of Financial Distress, that are Zmijewski Model, Fulmer Model, Grover Model, Altman Z-Score Model, and Springate Model. Method: This study uses secondary data on the textile companies listed on the Indonesia Stock Exchange. The sample used in this study were five companies. The sample selection uses purposive sampling. This type of research used in this research is quantitative descriptive, namely research on problems in the form of the current facts of a population. Testing research data using data analysis of model financial distress. Findings: This study uses secondary data on the textile companies listed on the Indonesia Stock Exchange. The sample used in this study were five companies. The sample selection uses purposive sampling. This type of research used in this research is quantitative descriptive, namely research on problems in the form of the current facts of a population. Testing research data using data analysis of model financial distress.

Detection of Financial Distress in Air Transportation Companies Registered in BEI Before and During Covid-19

Financial distress analysis aims to identify and analyze financial distress in air transportation companies listed on the Indonesia Stock Exchange before and during Covid-19 with two airlines in Indonesia with CMPP and GIAA issuer codes. The research method used is descriptive method with a quantitative approach. The data used is secondary data in the form of company financial reports as objects of research for the period 2016 to 2021. Data analysis uses the Altman Z-Score model with the formula for calculating four financial ratios. The results of the study show that before and during Covid-19, CMPP and GIAA issuers were in a position of financial distress or entered a distress zone with a Z-Score value of less than 1.10 (Z <1.10)

ANALISIS FINANCIAL DISTRESS PADA PERUSAHAAN PERBANKAN SYARIAH YANG TERDAFTAR DI BURSA EFEK INDONESIA

The study was conducted to analyze financial distress at 4 Islamic banks listed on the Indonesia Stock Exchange. The four banks became the population and sample in this study, which consisted of PT. Bank Syariah Indonesia Tbk (BRIS), PT. Bank Aladin Syariah Tbk (BANK), PT. Bank BTPN Syariah Tbk (BTPS) and PT. Bank Panin Dubai Syariah Tbk (PNBS). The data used is secondary data from the Financial Services Authority website for 2016-2021. The data analysis technique uses financial distress analysis with the Springate model. The research results obtained that only PT. Bank Syariah Indonesia Tbk (BRIS) for 2016-2021 is in good condition. PT. Bank Aladin Syariah Tbk (BANK) in 2016, 2018 and 2021 with results of S < 0.861 so that it can be declared unhealthy or experiencing financial difficulties. Likewise with PT. Bank BTPN Syariah Tbk (BTPS) also experienced financial difficulties in 2018 and 2018 with an S value <0.862. Then PT. Bank Panin Dubai Syariah Tbk (PNBS) in 2017 and 2021 also obtained an S value <0.862. This is because the Bank obtains a negative profit value or suffers a loss.

Comprehensive Analysis of Financial Distress of the Tourism and Transportation Sector Using Financial Discriminant Models Pre and During the Covid-19 Pandemic

This study aims to analyze and compare the financial condition of tourism and transportation sector companies listed on the Indonesia Stock Exchange before and during COVID-19 using the Altman, Springate, Zmijewski, and Grover models. The type of research used is comparative descriptive research. This comparative study aims to compare the financial health of the tourism and aviation sectors before and during COVID-19. The source of data in this study was obtained from the IDX website, namely http://www.idx.co.id. Data analysis using the Z Score method Altman, Springate, Zmijewski and Grover to determine the financial condition then perform individual and comparative analysis. The results of the study stated that using the four Z-score methods Altman, Springate, Zmijewski, and Grover, the financial condition of the transportation and tourism sectors had decreased financial health since the onset of COVID-19. Where the tourism and transportation sectors before the Covid-19 outbreak were on average safe but after the Covid-19 the level of distress experienced an increase and their safe position decreased. This is because during the Covid-19 period there was a government policy to limit travel and crowds in the community. Where the government implements PSBB policies, transitional PSBB, emergency PPKM to four-level PPKM so that people do not dare to travel and this has a huge impact on the transportation and tourism sectors

Prediction of Bankruptcy Risk Using Financial Distress Analysis

Financial distress analysis using X-Score Zmijewski model, Z-Score Altman model, and S-Score model Springate is intended to determine the potential for bankruptcy at PT. Hero Supermarket, Tbk. Secondary data was used in the 2016-2020 financial statements. The results of the calculation of the X-Score method from 2016 - 2019 were in a non-financial distress condition, but in 2020 they were in a distressed situation. This follows the X-Score principle, which focuses on the company's liabilities. We decrease the safe zone to the danger zone from the Z-Score method. In the S-Score process, the company can go bankrupt. The analysis results of the three ways conclude that the company is experiencing financial difficulties. Fast and appropriate handling is needed to fix its condition, and management must improve financial performance. Company management must improve financial conditions, significantly reducing total liabilities every year. The actual existing company liabilities are not more significant than the income earned, so that the level of losses that will be experienced will be reduced. Furthermore, the company should conduct a company evaluation of efforts to improve operational and financial performance as response to the company’s financial condition. So that, the economic distress experienced can be appropriately resolved.

Analysis of financial distress in banking companies listed on the indonesian stock exchange

Financial distress is a condition when a company experiences an inability to fulfill all financial obligations in the long term. This study analyzes capital structure, female directors, liquidity, and profitability predicting the possibility of financial companies in the 2018-2020 period experiencing financial distress. The research population is financial companies operating on the IDX in the 2018-2020 period with as many as 105 companies. Determination of the sample used is purposive sampling method with the results of 46 companies. The research analysis technique is panel data regression with the best fixed effect model. Based on the analysis results show that the capital structure has a significant effect on financial distress where the higher the company's leverage will cause financial distress. While female director, liquidity, and profitability have no significant effect on the company's financial distress. It is expected that the company will always pay attention to the level of use of leverage so that it can maintain the optimal condition of the company's cash. For future research, it is possible to add variables such as inflation rate, interest rate, tax, firm size, growth sales which can affect financial distress. Â

An Empirical Test of The Financial Ratio Effect on Financial Distress in Indonesia (Study in Garment and Textile Industry)

This research aims to investigate the impact of the current ratio (CR), debt to asset ratio DA), and return on assets (ROA) on financial distress. The measure of financial distress level is the Altman Z-score index. The sampling technique in studies is purposive sampling. The sample is 16 textile companies and 80 firm-year observations. The result of data analysis indicates that the current ratio (CR), debt to the asset (DA), and return on assets (ROA) significantly influence financial distress (Z-Score rating). The partially current ratio and return on assets positively affect financial distress (Z-Score Index). The debt to asset ratio has a significant negative effect on financial distress (Z-Score Index). The finding contributes to the company's management considering these three ratios in making business decisions to avoid financial distress. The originality of this study is the analysis of financial distress from the textile and garment industry in the Indonesian capital market.

Analisis Financial Distress pada Perusahaan Sub Industri Penerbangan dan Kereta Api yang Terdaftar di Bursa Efek Indonesia Sebelum dan Sesudah Pandemi Covid-19

The Covid-19 pandemic has impacted all fields, including the airline and railway industries. One of the impacts is the decrease in passengers causes the company's income to decline. This condition can make the companies face financial difficulties, which can end in bankruptcy. This research aims to analyze the financial distress in the sub-industry companies before and after the Covid-19 pandemic, especially in the airline and railway industries listed on the Indonesian stock exchange using the Altman Z-Score and Springate methods. The type of research used is descriptive quantitative with purposive sampling technique in taking the samples. Data are collected by applying the documentation technique with secondary data in quarterly financial reports from 2018 to 2021. The research sample amounted to four companies. The research shows that the Altman Z-Score and Springate methods used in the analysis of financial distress before and after the Covid-19 pandemic in four companies present the same results in which the companies entered a dangerous zone because of the decline in the income. Future research is recommended to use other methods to analyze financial distress and expand the research population or other companies. Keywords: The Covid-19 Pandemic, Financial Distress, Altman Z-score, and Springate

Analisis Rasio Keuangan Untuk Memprediksi Kondisi Financial Distress (Studi Empiris Pada Perusahaan Property dan Real Estate yang Terdaftar Di BEI Tahun 2018-2020)

<p><em>This study aims to compare which financial distress analysis model is the best and provide evidence of whether financial ratios have an effect on predicting financial distress conditions in companies. The population in this study are property and real estate companies listed on the Indonesia Stock Exchange from 2018 to 2020. The sampling method used is purposive sampling. The sample used in this study was 35 companies with an observation period of 3 years with sampling criteria. The type of data used is secondary data. The analytical method used in this research is logistic regression analysis with statistical techniques and descriptive analysis. The results of this study indicate that (1) Return On Equity (ROE) has a significant effect in predicting financial distress conditions; (2) Current Ratio (CR), Debt to Asset Ratio (DAR), Debt to Equity Ratio (DER), Current Liabilities to Total Asset Ratio (CLAR), and Return On Assets (ROA) have no significant effect in predicting financial distress. ; (3) Grover Method is the most significant method to be used in predicting financial distress conditions in property and real estate companies listed on the Indonesia Stock Exchange in 2018-2020.</em></p>

Financial Distress dan Managemen Laba pada Industri Jasa Trasportasi di Masa COVID-19

This study detects financial distress and the existence of earnings management which is classified into accrual and real earnings management in the transportation service industry. The data analysis technique was carried out using Altman's financial distress analysis, followed by linear regression analysis with quantitative descriptive methods. Purposive sampling method was used and the research sample obtained was eight companies with a total of 48 observational data. The results showed that transportation companies at various levels of financial distress were proven to practice accrual earnings management. However, there are differences in the choice of accrual earnings management strategies at each level of distress. In companies that are in advanced distress level, accrual earnings management is carried out by means of income maximization and followed by the practice of big bath. Meanwhile, in extreme distress, the company decides to do income minimization.
 Keywords: Financial Distress; Accrual Earnings Management; Real Earnings Management.

Financial Distress Analysis with Springate and Zmijewski Model at PT. Smartfren Telecom, Tbk and PT. Bakrie Telecom.Tbk

Financial distress is a situation where companies are experiencing financial difficulties that can lead companies to go failed. Springate and Zmijewski models are models that can be used to assess the financial distress in a company. Problems in this research lies in the object of research where PT. Smartfren Telecom, Tbk and PT. Bakrie Telecom, Tbk is a telecommunication company that uses CDMA network. This company suffered losses since 2011 but still able to stand up to now. The purpose of this study to determine financial distress at PT. Smartfren Telecom, Tbk and PT. Bakrie Telecom, Tbk using Springate and Zmijewski models for 6 periods starting from 2011-2016. The type of research data is secondary data that is financial statements of PT. Smartfren and PT. Bakrie Telecom, Tbk. Data collection method is literature study. The method of research analysis is quantitative descriptive method.Based on the results of research by using Springate model, it can be concluded that PT. Smartfren Telecom, Tbk and PT. Bakrie Telecom, Tbk experienced financial distress from 2011-2016. Financial distress caused the company suffered losses from 2011 to 2016. While using the model Zmijewski, PT. Smartfren Telecom, Tbk. experiencing financial distress in 2012 and 2015. While PT. Bakrie Telecom, Tbk. experienced financial distress in 2011. This condition is due to higher operational and non-operating expenses than on sales (overload). The Company has difficulty in controlling operating expenses. In addition, working capital is negative. This is because current assets are lower than current liabilities.