scholarly journals An Analysis of the Predictors of Financial Distress for Zimbabwe Listed Corporates

2021 ◽  
pp. 1-14
Author(s):  
Louisa Muparuri ◽  
Victor Gumbo
Keyword(s):  
Artificial Intelligence ◽  
Time Series ◽  
Performance Indicators ◽  
Financial Distress ◽  
Stock Exchange ◽  
Binary Logistic Regression ◽  
Book Value ◽  
Future Studies ◽  
Time Series Dataset ◽  
Corporate Distress

This study brings novelty to the area of corporate distress modelling in Zimbabwe by exploring company-specific indicators of corporate distress, unlike most of the previous studies, which used financial performance indicators. Using a binary logistic regression on a time series dataset collated between 2010 and 2017, this study establishes book value, book value per share, average debt to equity and equity per share as very significant determinants of corporate distress on the Zimbabwe Stock Exchange (ZSE). Future studies incorporating artificial intelligence and a combination of both the traditional financial ratios and market-based indicators is recommended to expand the scope of the study.

scholarly journals Profitabilitas Memoderasi Pengaruh Financial Distress pada Opini Audit Going Concern

2019 ◽  
Vol 29 (1) ◽  
pp. 420
Author(s):  
Anak Agung Gde Oka Maheswara ◽  
A.A. Ngurah Bagus Dwirandra
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Participant Observation ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Binary Logistic Regression Analysis ◽  
Manufacturing Companies ◽  
Audit Opinion ◽  
Going Concern ◽  
Observation Methods

The purpose of this study was to determine the effect of partial financial distress on the going concern audit opinion, to determine the effect of partial profitability on the going concern audit opinion and to know the moderating ability of profitability on financial distress that affects the going concern audit opinion. This research conducted at manufacturing companies listed on the Stock Exchange in 2015-2017. The research sample was obtained using purposive sampling technique. Data collection is done by non-participant observation methods. Data analysis techniques are carried out using the method of binary logistic regression analysis. The test results show that financial distress has an effect on the going concern audit opinion, profitability has no effect on the audit opinion, and profitability weakens the effect of financial distress on the going concern audit opinion. Keywords : Financial Distress; Going Concern Audit Opinion; Profitability.

scholarly journals Forecasting Model for Stock Market Based on Probabilistic Linguistic Logical Relationship and Distance Measurement

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 954
Author(s):  
Aiwu Zhao ◽  
Junhong Gao ◽  
Hongjun Guan
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Exchange ◽  
Forecasting Model ◽  
Historical Time ◽  
Logical Relationship ◽  
Probabilistic Linguistic Term Set ◽  
Time Series Dataset ◽  
Proposed Model ◽  
Linguistic Term

The fluctuation of the stock market has a symmetrical characteristic. To improve the performance of self-forecasting, it is crucial to summarize and accurately express internal fluctuation rules from the historical time series dataset. However, due to the influence of external interference factors, these internal rules are difficult to express by traditional mathematical models. In this paper, a novel forecasting model is proposed based on probabilistic linguistic logical relationships generated from historical time series dataset. The proposed model introduces linguistic variables with positive and negative symmetrical judgements to represent the direction of stock market fluctuation. Meanwhile, daily fluctuation trends of a stock market are represented by a probabilistic linguistic term set, which consist of daily status and its recent historical statuses. First, historical time series of a stock market is transformed into a fluctuation time series (FTS) by the first-order difference transformation. Then, a fuzzy linguistic variable is employed to represent each value in the fluctuation time series, according to predefined intervals. Next, left hand sides of fuzzy logical relationships between currents and their corresponding histories can be expressed by probabilistic linguistic term sets and similar ones can be grouped to generate probabilistic linguistic logical relationships. Lastly, based on the probabilistic linguistic term set expression of the current status and the corresponding historical statuses, distance measurement is employed to find the most proper probabilistic linguistic logical relationship for future forecasting. For the convenience of comparing the prediction performance of the model from the perspective of accuracy, this paper takes the closing price dataset of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) as an example. Compared with the prediction results of previous studies, the proposed model has the advantages of stable prediction performance, simple model design, and an easy to understand platform. In order to test the performance of the model for other datasets, we use the prediction of the Shanghai Stock Exchange Composite Index (SHSECI) to prove its universality.

scholarly journals Analisis Perbandingan Financial Distress Pada Perusahaan Sub Sektor Rokok Periode 2015-2019

2021 ◽  
Vol 3 (3) ◽  
pp. 157-163
Author(s):  
Anang Makruf ◽  
Deni Ramdani
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Market Value ◽  
Sampling Technique ◽  
Z Score ◽  
Book Value ◽  
Purposive Sampling ◽  
Quantitative Models ◽  
A Company ◽  
Analyze Data

Abstract – The aim of the study was to analyze financial distress in cigarette companies list in Indonesia Stock Exchange in 2015-2019 using 3 methods, Altman Z-Score, Zmijewski, and Springate. Purposive sampling is used in this study to determine the sampling technique. The sample used in this study released 4 cigarette companies. Descriptive asalysis with quantitative models was used to analyze data in this research. Altman Z-Score, Zmijewski, and Springate in 2015-2019 PT. HM Sampoerna Tbk, PT. Gudang Garam Tbk, and PT. Wismilak Inti Makmur Tbk is related to safe, but it is needed a company that is estimated to be grey in the Altman Z-Score calculation in 2018, PT. Wismilak Inti Makmur Tbk. The Z-score is at the limit because the companie has a ratio with a lower value in market value of equity  to book value of liabilities   Abstrak – Penelitian ini memiliki bertujuan untuk menganalisis perbandingan kesulitan keuangan dalam perusahaan sun sektor rokok di Indonesia Stock Exchange periode 2015-2019 menggunakan tiga metode. Metode yang digunakan yaitu Altman Z-Score, Zmijewski, dan Springate. Purposive sampling digunakan dalam penelitian ini untuk menentukan teknik pengambilan sampel. Sampel yang digunakan berjumlah 4 perusahaan rokok. Analisis deskriptif dengan pendekatan kuantitatif digunakan sebagai teknik analisis data. Dalam penelitian ini menjelaskan financial distress yang dihitung menggunakan metode Altman Z-Score, Zmijewski , dan Springate pada tahun 2015-2019 PT. HM Sampoerna Tbk, PT. Gudang Garam Tbk, dan PT. Wismilak Inti Makmur Tbk mengalami dalam kondisi keuangan yang sehat, namun terdapat perusahaan yang diestimasi rawan kebangkrutan pada perhitungan Altman Z-Score pada  tahun 2018 yaitu PT. Wismilak Inti Makmur Tbk. hal ini dapat terjadi  karena nilai Z-Score PT. Wismilak Inti MakmurTbk  berada pada Z < 1,81 salah satu penyebabnya ialah rendahnya rasio market value of equity terhadap liabilities.

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 Perbandingan Kinerja Saham Syariah di Bursa Efek Indonesia dan Bursa Malaysia

2019 ◽  
Vol 10 (2) ◽  
pp. 82
Author(s):  
Hisbullah Basri ◽  
Veny Mayasari
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Cross Section ◽  
Stock Exchange ◽  
Secondary Data ◽  
Risk Difference ◽  
T Test ◽  
Stock Performance ◽  
Book Value ◽  
Purposive Sampling

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>ABSTRACT</span></p><p><span>This research aims to determine the difference in Sharia stock performance in the Indonesia Stock Exchange and Bursa Malaysia. The population in the study is all sharia stocks listed on the Indonesia Stock Exchange and Bursa Malaysia amounting to 1,280 Sharia shares. The retrieval technique uses purposive sampling where the samples are taken with certain criteria. Meanwhile, the research sample amounted to 60 Sharia shares in which 30 sharia stocks are found on the Indonesia Stock Exchange and 30 Sharia shares in Bursa Malaysia. The research uses four indicators to use the stock performance of Return shares, Price Earning Ratio (PER), Price to Book Value (PBV), and Earning per Share (EPS). The data analysis method used in this study is quantitative analysis. The data used is secondary data, time series, and cross-section. The data analysis technique used is by conducting independent sample T-Test. The results showed that there was no difference in the performance of sharia stocks on the Indonesia Stock Exchange and Bursa Malaysia given price to book Value (PBV) and Price Earning Ratio (PER) with significance values of 0.308 and 0.264 respectively. As for the performance of shares with indicators return and EPS obtained the result that there is a difference in the performance of sharia stocks on the Indonesian stock exchange with significance values of 0.006 and 0.000 respectively. This difference is more due to the risk difference in Indonesia and Malaysia.</span></p><p><span>Key words </span><span>: Stock Performance, Return, EPS, PBV, PER</span><span>ABSTRAK</span></p><p><span>Penelitian ini bertujuan untuk mengetahui perbedaan kinerja saham syariah di Bursa Efek Indonesia dan Bursa Malaysia. Populasi pada penelitian adalah seluruh saham syariah yang terdaftar di Bursa Efek Indonesia dan Bursa Malaysia yang berjumlah 1.280 saham syariah. Teknik pengambilan menggunakan purposive sampling dimana sampel diambil dengan kriteria tertentu. Sedangkan sampel penelitian ini berjumlah 60 saham syariah dimana 30 saham syariah yang terdapat di Bursa Efek Indonesia dan 30 saham syariah yang terdapat di Bursa Malaysia. Penelitian ini menggunakan empat indikator untuk menggukur kinerja saham yaitu Return Saham, Price Earning Ratio (PER), Price to Book Value (PBV), dan Earning per Share (EPS). Metode Analisis data yang digunakan dalam penelitian ini adalah analisis kuantitatif. Data yang digunakan adalah data sekunder, time series dan cross section. Teknik analisis data yang digunakan yaitu dengan melakukan independent sampel t-test. Hasil penelitian menunjukkan bahwa tidak terdapat perbedaan kinerja saham syariah di Bursa Efek Indonesia dan Bursa Malaysia di lihat dari price to book Value (PBV) dan Price Earning Ratio (PER) dengan nilai signifikansi masing-masing sebesar 0,308 dan 0,264. Sedangkan untuk kinerja saham dengan indikator return dan EPS didapat hasil bahwa terdapat perbedaan kinerja saham syariah di Bursa Efek Indonesia dengan nilai signifikansi masing-masing sebesar 0,006 dan 0,000.</span></p><p><span>Kata kunci</span><span>: Kinerja Saham, Return, EPS, PBV, PER</span></p></div></div></div>

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI FINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR DI INDONESIA

2019 ◽  
Vol 4 (1) ◽  
pp. 19-28
Author(s):  
Muhammad Rizali Fadlillah
Keyword(s):  
Significant Influence ◽  
Financial Distress ◽  
Quantitative Methods ◽  
Firm Growth ◽  
Stock Exchange ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Manufacturing Companies ◽  
Operating Capacity ◽  
Sample Technique

This study conducted to understand and get empirical evidence from the effect of factors which represented by Liquidity, Leverage, Operating Capacity, Profitability and Firm Growth on Financial Distress at manufacture companies which listed on Indonesia Stock Exchange from 2015-2017. This study is an associative research category. This study uses quantitative methods to determine the effect of a variable on other variables. All of manufacturing companies which listed on the Indonesia Stock Exchange in the period 2015 to 2017 are the population of this study. Then, the number of samples used are 101 companies which purposive sampling as the sample technique. Samples are selected using the specified criteria.The factors that become the variables in this research are liquidity, leverage, operating capacity, profitability and firm growth as independent variables, and financial distress as dependent variable. This research used secondary data. The data analysis technique used binary logistic regression supported by SPSS version 23. The result of this research showed that liquidity, leverage, operating capacity, and profitability have significant influence on the condition of financial distress of manufacturing companies listed in Indonesia Stock Exchange. Meanwhile, firm growth do not have significant influence on the condition of financial distress of manufacturing companies listed in Indonesia Stock Exchange.

scholarly journals DETERMINAN TERHADAP PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR DI BURSA EFEK INDONESIA

2015 ◽  
Vol 15 (2) ◽  
pp. 371
Author(s):  
Raissa Karina Loman ◽  
Mariana Ing Male
Keyword(s):  
Firm Size ◽  
Financial Distress ◽  
Stock Exchange ◽  
Binary Logistic Regression ◽  
Institutional Ownership ◽  
Sales Growth ◽  
Financial Leverage ◽  
Stock Volatility ◽  
Insider Ownership ◽  
Purposive Sampling

ABSTRACT This study aims to look at the effect of insider ownership, institutional ownership, firm size, sales growth, stock volatility and financial leverage to prediction of financial distress on manufactur companies listed in Indonesia Stock Exchange. Financial distress is a condition where a company having a financial difficulties. Data sample studied were enrolled in manufactur companies listed in Indonesia Stock Exchange during the period 2008-2013 selected by purposive sampling method. The method of data analysis is done by using binary logistic regression.     The results show that institutional ownership, firm size, sales growth, stock volatility and financial leverage partially have significant effect on financial distress, while insider ownership partially have no significant effect on financial distress. Insider ownership, institutional ownership, firm size, sales growth, stock volatility and financial leverage together have significant effect on financial distress.      ABSTRAKSIPenelitian ini bertujuan untuk melihat pengaruh insider ownership, institutional ownership, firm size, sales growth, stock volatility dan financial leverage terhadap prediksi financial distress pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia. Financial distress adalah keadaan dimana suatu perusahaan mengalami kesulitan keuangan. Sampel data yang diteliti adalah perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia periode 2008-2013 yang diseleksi menggunakan purposive sampling. Metode analisis data dilakukan dengan menggunakan regresi logistik biner.Hasil penelitian ini menunjukkan bahwa institutional ownership, firm size, sales growth, stock volatility dan financial leverage secara parsial berpengaruh signifikan terhadap financial distress sedangkan insider ownership secara parsial tidak berpengaruh signifikan terhadap financial distress. Insider ownership, institutional ownership, firm size, sales growth, stock volatility dan financial leverage secara bersama-sama berpengaruh signifikan terhadap financial distress. 

scholarly journals The role of moderating audit quality relationship between corporate characteristics and financial distress in the Indonesian mining sector

2020 ◽  
Vol 17 (2) ◽  
pp. 88-100
Author(s):  
Perdana Wahyu Santosa ◽  
Martua Eliakim Tambunan ◽  
Eva Rohima Kumullah
Keyword(s):  
Corporate Governance ◽  
Financial Distress ◽  
Audit Quality ◽  
Stock Exchange ◽  
Binary Logistic Regression ◽  
Financial Statements ◽  
Binary Logistic Regression Model ◽  
Mining Sector ◽  
Managerial Implications

Financial performance and corporate governance play an important role in financial distress in the mining sector, which is one of the most significant contributors to the Indonesian economy. This study aims to analyze the effect of corporate characteristics on financial distress (FD), which is moderated by corporate governance (audit quality), and uses the controlling variables (inflation rate and GDP). The study uses data from audited financial statements from mining sector in the Indonesia Stock Exchange for the period 2013–2018. Since the dependent variable (FD) is dichotomous, this study used a binary logistic regression model, as it is the case in many studies regarding the probability of bankruptcy filing. In line with the current study and some previous studies, leverage, efficiency (activity), market-to-book value, audit quality, and GDP affect the probability of financial distress significantly. Only liquidity and inflation do not impact FD. Besides, the moderating audit quality weakens the effect of liquidity and PBV; otherwise, it strengthens leverage and efficiency in predicting financial distress. As for managerial implications, this study concludes that corporate performance, corporate governance, and macro-risk factors affect the probability of financial distress. The authors suggest that mining firms need to pay attention to corporate governance and should watch the economic condition for business sustainability.

scholarly journals MODEL PREDIKSI KESULITAN KEUANGAN DENGAN RASIO KEUANGAN (Studi kasus Pada Perusahaan Manufaktur di Indonesia yang telah terdaftar selama 5 Tahun di BEI 2008-2012)

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Diaz Lunardi Santoso
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Manufacturing Industry ◽  
Sampling Method ◽  
Stock Exchange ◽  
Market Value ◽  
Financial Ratios ◽  
Predicting Model ◽  
Book Value ◽  
Purposive Sampling

This research aimed to figure financial distress model and to determined wihich financial ratios can predict financial distress for 1 year; 2 years; and 3 years before. This research was using samples of manufacturing industry thst listed on The Indonesian Stock Exchange in 2008-2012. Based on purposive sampling method, the research samples total are 160 manufactured companies. To figure the model, this research used logistic regression. This research indicated that financial ratios likes leverage, profitability, activity, RE to Total Assets, Market value of Equity to Book Value of Debt can predict financial distress 1 year; 2 years; and 3 years before. These financial ratios can predict above 64% of financial distress for 1 year; 2 years, and 3 years before, while around 36% were influeced by others factors. The predicting model for 1 year have 96,3% clasification accuracy ,while 2 years model have 96,3% clasification accuracy and 3 years model  have 92,5% clasification accuracy

scholarly journals ANALISIS FINANCIAL DISTRESS PADA PERUSAHAAN BATUBARA YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2011 - 2014

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Tiodorma Br. Sijabat ◽  
Cut Ermiati
Keyword(s):  
Stock Prices ◽  
Financial Distress ◽  
Stock Exchange ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Financial Ratios ◽  
Book Value ◽  
Corporate Earnings ◽  
Score Model ◽  
Retained Earnings

The purpose of this study was to determine whether the financial ratios in Altman can explain financial distress. There are five financial ratios in Altman, which is the ratio of Net Working Capital to Total Assets (X1), Retained Earnings to Total Assets (X2), Earnings Before Interest and Tax to Total Assets (X3), Market Value of Equity to Book Value of Total Debt (X4) and Sales to Total Assets (X5). The population in this study are listed coal company in Indonesia Stock Exchange period 2011 - 2014. This study used purposive sampling method of sampling so that there are 18 companies. The data used is secondary data that is accessed from the website www.idx.co.id. The analytical method used is descriptive analysis. The results of this study for five years of observation, the financial ratios in Altman can explain financial distress in the coal company listed on the Indonesia Stock Exchange. The coal company in this study more companies to financial distress or equivalent to 56.67 % of the company.Where it can be seen from the decline in corporate earnings and some have suffered losses in recent years, the decline in the sales of the company, the amount of the costs the company the amount of debt continues to rise and stock prices continue to fall in the capital market. Keywords: Financial Ratios, Altman Z-Score Model, Financial Distress

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