Analysis Of Financial Distress Research Articles

Financial Distress Analysis to Predict Company Bankruptcy Using the Modified Altman Method

Financial distress is a condition where the company experiences a decline in its financial condition before bankruptcy. To avoid this condition, the company must pay attention to its financial condition both in terms of its balance sheet and income statement using financial statement analysis techniques, such as the Altman model. The purpose of this study is to analyze the occurrence of Financial Distress to predict company bankruptcy using the Modified Altman method using 3 classification categories namely safe, gray, and distress. A quantitative approach was used in this study with a total population of all companies listed on the JII and the sample selection using a purposive sampling technique so that a sample of 13 companies was obtained. Based on the Altman Z-score analysis, the results show that: 8 companies are consistently in the Safe category for 5 years with a cut-off value> 2.9. Then, if analyzed as a whole, the mean value obtained from all companies is 5.7688> 2.9. This value illustrates that on average all companies listed on the Jakarta Islamic Index in 2018-2022 are in the safe category.

Financial Distress Analysis in Detecting Bankruptcy Levels in Manufacturing Companies

The methodology used is the Altman method, the Springate method and the Zmijewski method for the 2015-2019 period. The type of data used is quantitative data. The data analysis technique used is the formula of the Altman method, the Springate method and the Zmijewski method. The results of this study show that in the 2015 and 2019 Altman method there are eight or all companies that are predicted to be in the bankrupt category. Meanwhile from 2016 to 2018 there are only six companies that are included in the bankrupt category and two other companies are categorized in the gray zone. In the Springate method from 2015 to 2019, there are eight or all companies predicted to have the potential to go bankrupt. In the zmijewski method from 2015 to 2017 there were five companies that were in the bankrupt category while in 2018 to 2019 there were only two companies that were included in the bankrupt category. In addition, based on the different results through the one-way ANOVA test, a significant value <0.05 was obtained, which means that there was a significant difference between the methods tested.

Financial Distress During the COVID-19 Pandemic: Altman and Springate Model Prediction

Background: The retail trade industry has experienced a sharp decline in economic growth during the COVID-19 pandemic. Regulation of social distancing, restrictions on retail shop operating hours, and disruption of online shopping behavior contribute to worsen the financial performance of retail trade companies. </p> <p> Purpose: The purpose of this research is to analyze the prediction of financial distress of retail trade companies. This research chose to use the Altman and Springate Model since both of them are the most accurate and conservative models to predict. </p> <p> Research Methodology: The financial distress analysis technique used is Altman and Springate Model. The calculation of the Altman and Springate Score is based on an equation formula for data in the period before and during the COVID-19 pandemic. The Altman’s Score are grouped in the Safe Zone, Grey Area, and Financial Distress; while the Springate’s Score are grouped in the Safe Zone and Financial Distress categories. </p> <p> Findings: Altman Model Analysis stated that most of the companies experienced a decreased scores, the company’s financial performance during COVID-19 pandemic was predicted financial distress and belong to the Grey Zone category than before COVID-19 pandemic. Springate Model Analysis states that all companies have decreased scores, and the company’s financial performance during COVID-19 pandemic is predicted financial distress than before COVID-19 pandemic. Springate Model revealed a more conservative indicator, but both models stated there were still exist several companies in the Safe Zone category to continue their business. </p> <p> Research limitations: The limitations of this study are only using Altman and Springate Model. The object of this research is the retail trade industry only, then future research may be able to expand the analyzed industry in the new normal conditions. </p> <p> Originality/value: The originality of this research is focused on the retail trade companies as the most affected industry by COVID-19 pandemic. In addition, this research analyzes financial distress based on Altman Z-Score and Springate Model as the most powerful model to predict.

Analysis Of Financial Distress In The Covid 19 Pandemic Era

This research aims to find out (1) find out whether there are differences in scores between the Altman, Springate, Zmijeski, and Grover models in predicting Financial Distress, (2) find out which companies remain healthy (green area) or do not experience Financial Distress and which companies which ones are unhealthy (red are) or experiencing Financial Distress. This research uses data from company financial reports with Special Notifications published on the Indonesia Stock Exchange website for 2020-2021. The sampling technique used purposive samples to obtain 10 companies that could be used as research. The results of this research show that the Altman model and the Grover model have the same score, namely an accuracy level of 40% and an error type of 20%, followed by the Zmijewski model with an accuracy rate of 30% and an error type of 30% and the Springate model an accuracy rate of 10% and an error type of 30%.

Analisis Model Grover, Altman, Springate dan Zmijewski Dalam Memprediksi Financial Distress Pada Perusahaan Sektor Transportasi, Logistik, Real Estate, dan Property

This final assignment aims to determine the financial condition of companies in the logistics transportation, real estate and property sectors listed on the Indonesia Stock Exchange for the 2018-2022 period, using a purposive sampling method with a total sample of 36 companies (180 data per company year). The type of data used is secondary data obtained from the company's financial reports. This research uses 4 financial distress analysis models, namely the Grover, Altman, Springate, and Zmijewski models. The results of this research show that the Grover and Altman model produces the same pattern, where the transportation and logistics sector is predicted to be in a distressed condition, while the real estate and property sector is predicted to be in a non-distressed condition. The Springate model produces a different pattern where the transportation logistics, real estate and property sectors are more dominantly predicted to be in distress. Meanwhile, the Zmijewski model for companies in the transportation logistics, real estate and property sectors is predicted to be in a non-distress condition. Overall, the transportation and logistics sector experienced distress of 67% and 34% for the real estate and property sectors.

Financial Distress Analysis using The Altman Z – Z-Score Method in Hotel Companies Listed on The Idx

The purpose of this study was to determine the business continuity of PT. Eastparc Hotel Tbk, PT. Bukit Uluwatu Village Tbk and PT. Hotel Sahid International Tbk uses secondary data as financial statements for 2019 – 2021. This study uses the Altman Z Score method, which is one method for assessing a company's bankruptcy. The covid 19 pandemic caused a significant decrease in performance at PT. Bukit Uluwatu Village Tbk Z. Z Score PT. Bukit Uluwatu Village Tbk in 2020 was -2.91, it decreased from 0.35 in 2019. Such conditions indicate that PT. Bukit Uluwatu Village Tbk experienced financial distress

Analysis of Financial Distress, Profitability, Liquidity, Leverage on Share Prices of Manufacturing Companies Listed on the IDX

The aim of this research is to determine the influence of the variables Financial distress, profitability, liquidity and Leverage on Manufacturing stock returns on the IDX in 2020-2021, in the phenomenon there are differences between real data and theory as well as research gaps that exist in previous research. The sampling method uses a purposive sampling method. The analysis technique used in this research uses Eviews Panel Data Regression Analysis version 12 and a significance level of 5% and in selecting the model the Chow test, Hausman test and Lagrange Multiplier test are used, which is better. The research results show that financial distress calculated using the Taffler model has a significant influence on stock returns with a significance value of 0.0022. Meanwhile, Profitability, Liquidity, Leverage have no effect and are not significant on stock returns

Analisis Financial Distress dengan Metode Altman Z-Score Modifikasi, Grover dan Zmijewski pada KSPPS BMT Ummat Sejahtera Abadi Jepara Tutup Tahun Buku 2018 – 2022

The purpose of this study was to recognize early warning signs of bankruptcy through financial distress analysis at KSPPS BMT Ummat Sejahtera Abadi Jepara by applying the Modified Altman Z-Score Method, the Grover Method and the Zmijewski Method. The type of research applied is quantitative research with descriptive descriptions. The object of research is the financial reports of KSPPS BMT Ummat Sejahtera Abadi Jepara at the close of the 2018 - 2022 financial year. The statistical study in this study uses the calculation of financial ratios at KSPPS BMT Ummat Sejahtera Abadi from the financial distress analysis method. The conclusion of the study showed that KSPPS BMT Ummat Sejahtera Abadi Jepara did not face financial distress in the results of the modified Altman Z-Score method above the cut off value > 2.60, the score for 5 consecutive years was 3.7. 3,825. 4,145. 4,027. 3,978. The same results show that the KSPPS BMT Ummat Sejahtera Abadi Jepara is in good health with the score on the Grover Method showing a number above the cut off G ≥ 0.01, namely 2018 (0.76), 2019 (0.77), 2020 (0.84) , 2021 (0.79), 2022 (0.799). Likewise the score on the Zmijewski Method shows a number less than 0, namely -3.28. -3.40. -3.62. -3.97. -3.95 means that KSPPS BMT Ummat Sejahtera Abadi Jepara is in good health, not facing financial distress and far from symptoms of bankruptcy.

The Comparative Analysis of Financial Distress Precipitating Factors in Islamic Banking in Indonesia and Malaysia Based on Bankometer Variables

This study seeks to identify and compare descriptively the factors that influence the likelihood of financial distress in Indonesian and Malaysian Islamic banking. This study selected some variables and standard ratio values based on the Bankometer model such as Islamic banks’ capital adequacy, leverage level, credit risk, efficiency, and liquidity. The financial ratio data collected from published financial reports from five Indonesian Islamic banks and four Malaysian Islamic banks then analyzed using binary logistic regression. The results indicate that during the observation periods, the capital level (CA and CAR), leverage level (EA), and credit risk (NPF) of Islamic banking in Indonesia and Malaysia met the Bankometer standard. Meanwhile, the liquidity level (LA) of Islamic banks in both countries slightly exceeded the Bankometer's maximum standard, especially before the pandemic period. The findings in this study may enrich the discourse on the factors that trigger possible financial distress in Islamic banking by collaborating with the Bankometer model and binary logistic regression.

Financial Distress Analysis with Firm Size as a Moderating Variable in the Restaurant, Hotel, and Tourism Sub-Sector Companies on the Stock Exchange of Indonesia

A financial distress decline in financial health a bussiness had before bankruptcy, so it is important for companies to analyze financial distress as a form of prevention from the start. The investigation’s goal was to examine financial distress using financial ratios that were tempered by firm size. The sample for this analysis consists of 41 firms operating in the restaurant, hotel, and tourist industries that are listed on the Stock Exchange of Indonesia between 2018 - 2021. These studies used purposive sampling techniques to gather samples from 23 different businesses. The data testing procedure employs Moderated Regression Analysis (MRA) in SPSS Version 26. Profitability and leverage were shown to be major factors in the probability of financial trouble. There is little correlation between liquidity and the likelihood of economic hardship. Profitability and leverage can exacerbate financial difficulty, although a company's scale can mitigate this. However, the impact of liquidity on financial hardship can't be dampened by a company's size.

Analysis of Financial Distress in Predicting Bankruptcy in Investment Companies in 2016-2020

Analysis of Financial Distress in Predicting Bankruptcy in Investment Companies in 2016-2020

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.