Z-score Model Research Articles

Pengaruh karakteristik komite audit terhadap fraudulent financial reporting

Purpose : This study aimed to prove whether audit committees were proxied financial expertise and meetings related to fraudulent financial reporting. Research methodology: This type of research was quantitative descriptive with an evaluation model of Beneish M-Score and Altman Z-Score in predicting fraudulent financial reporting. The sample in this study was non-financial companies listed on the Stock Exchange with an observation period of 2010-2018. The technique of taking samples with purposive sampling obtained the number of observations 551. Data processing was done via SPSS through logistic regression. Results : The results of the study showed that the characteristic of the audit committee that influence the fraudulent financial reporting is financial expertise possessed by the members of the audit committee, while the number of audit committee meetings has no effect on the fraudulent financial reporting. Limitation: This study only used a sample of non-financial companies listed on the Indonesia Stock Exchange in 2010-2018 and met the criteria. The dependent variable fraudulent financial reporting measured through the Beneish M-Score and Altman Z-Score models. The independent variable was financial and or accounting expertise from the members of the audit committee and the Audit Committee Meeting. Contribution: Investors can consider this research in making decisions to be more careful in investing, as well as a reference for further research. The results of this study are expected to provide an overview and understanding of the role of the audit committee in suppressing fraudulent financial reporting using the Beneish M-Score and Altman Z-Score. Keywords: Fraudulent financial reporting, Audit committee characteristics, Leverage

Economic growth and financial performance of Islamic banks: a CAMELS approach

PurposeThe purpose of this paper is to investigate the link between the financial performance of Islamic finance and economic growth in all of Malaysia, Indonesia, Brunei, Turkey and Saudi Arabia within the endogenous growth model framework.Design/methodology/approachThis study applied dynamic panel system GMM to estimate the impact of the financial performance of Islamic finance on economic growth using quarterly data (2014:1-2018:4). CAMELS system parameters were employed as variables of the financial performance of Islamic finance and gross domestic product (GDP) as a proxy of economic growth. The sample contained all Islamic banks working in the five countries.FindingsThe findings demonstrated that the only significant factor of the financial performance of Islamic finance, which affects the endogenous economic growth, is profitability through return on equity (ROE). The experimental findings also indicated the necessity of stimulating other financial performance factors of Islamic finance to achieve a significant contribution to economic growth.Practical implicationsThe analysis in this paper would fill the literature gap by investigating the link between financial performance of Islamic finance and economic growth, as this study serves as a guide for the academians, researchers and decision-makers who want to achieve economic growth through stimulating Islamic finance in the banking sector. However, this study may well be extended to investigate the link between the financial performance of Islamic finance and economic growth over the Z-score model as another measure for the financial performance of Islamic finance.Originality/valueThis paper is the first that investigates the link between financial performance of Islamic finance and economic growth empirically using CAMELS parameters within the endogenous growth model to provide robust information about this link based on a sample of the top pioneer Islamic finance countries.

Bankruptcy Analysis Using Altman Z-Score Model and Springate Model In Retail Trading Company Listed In Indonesia Stock Exchange

The business environment in the retail experience turbulence, strong now many companies to reduce the impact outlets greater losses. Reduction in earnings a problem most of all , and this has potential in bankruptcy retail company in the future This research is analyzing about retail companies affected by the deterioration in performance that has been registered in Indonesia Stock Exchange. Model and data processing used to calculate potential harm is a model altman z score and models springate. Discussion result there is a retail companies go public has the potential to be the calculated use bankruptcy model altman z score as well as a model springate namely pt modern. international. Information , proceedings in potential for bankruptcy at annual report is not disclosure , was recommended to the stakeholders to oblige any new issuers give this information in the annual financial report made that release every year. To be accurate information and credible over the companies condition the truth.

Bankruptcy Analysis Using Altman Z-Score Model and Springate Model In Retail Trading Company Listed In Indonesia Stock Exchange

Bankruptcy Analysis Using Altman Z-Score Model and Springate Model In Retail Trading Company Listed In Indonesia Stock Exchange

Metode Altman Z-Skor Dalam Memprediksi Kepailitan Di Semua Koperasi Kredit Di Kabupaten Maumere

Abstract 
 Problems that often occur in a cooperative are usually caused by financial problems. To measure the level of financial health cooperatives can be used analysis of financial ratios using the Altman Z-Score model. This research aims to predict bankruptcy in the credit Union of the regional government Puskopdit, Maumere, using the Altman Z-Score model. The samples in this study were credit cooperatives of the main district Puskopdit in 2015-2017 consisting of 16 cooperatives. The data source used is the secondary data in the form of cooperative financial statements. The analytical technique used is the Altman Z-Score Bankruptcy Prediction model. The results showed that there is a cooperative that has been in the healthy category during the year 2015-2017, namely Torch Mas Cooperative, Tuke Jung, Ortal, Plantation, star East, and Serba Te. In the years 2015 and 2016 Kelubagolit cooperatives entered in the category of gray area, but in the year 2017 the cooperative is in a healthy category. In addition, there are cooperatives during the year 2015-2017 in the category of gray area namely Sube Huter Cooperative, Tuke Ler, Hiro Heling, Bina Pertiwi, and Surya Sakti. The cooperatives of San Dominggo in 2015 and 2016 were in the category of bankruptcy, but the following year entered the gray area category. The cooperative in the category of bankruptcy from 2015-2017 is the youth cooperative Hokeng and Ankara. In the year 2015 Plelu Meluk Cooperative entered in the category of gray area, the cooperative's performance continued to decline and in the year 2016 and 2017 the cooperative was entered in the category of bankruptcy. In the years 2018, Hokeng Youth Cooperative experienced an amalgamation with Mitan Gitan Cooperative. This indicates that the accuracy level of the Altman Z-Score model is high..

PENGENDALIAN INTERN KAS DALAM USAHA MENINGKATKAN EFISIENSI PENGGUNAAN DANA

The purpose of this study was to predict the level of bankruptcy in PT. HM Sampoerna, Tbk. and PT. Gudang Garam, Tbk. The type of data used is qualitative data and quantitative data. The data source used secondary data. The analytical method used is the Altman Z-Score method. The results of this study indicate that the results of the analysis of the Altman Z-Score on PT. HM Sampoerna, Tbk.and PT. Gudang Garam, Tbk. warehouse. In 2018-2019 shows good result, where both of these companies have Z-Score above 2,6. At PT. HM Sampoerna, Tbk. in 2018 the Z-Score was 12,0816 > 2,6. And in 2019 the Z-Score was 10,5251 > 2,6. While in PT. Gudang Garam ,Tbk. in 2018 the Z-Score was 7,3407 > 2,6 and in 2018 the Z-Score was 7,5251 > 2,6. So in the calculation of the Altman Z-Score model Altman Z-Score model that can predict bankruptcy Z-Score > 2,6 which in indicate by the company in a safe condition or non bankrupt. Keywords: Altman Z-score, bankruptcy prediction

Analisis Z-Score Untuk Memprediksi Tingkat Kebangkrutan Perusahaan (Studi Pada Industri Farmasi di Bursa Efek Indonesia Periode 2012-2014)

This study aims to determine the level of corporate bankruptcy using model analysis Altman Z-Score on pharmaceutical companies in Indonesia Stock Exchange (IDX) 2012-2014. The study population was all of the Pharmaceutical Industry with a sample of eight pharmaceuticalscompanies in the Indonesia Stock Exchange (IDX) in accordance with predetermined criteria. The results of this study indicate that the Altman Z-Score model can be implemented to detect the possibility of bankruptcy in the pharmaceutical company in Indonesia Stock Exchange (IDX). Altman Z-Score model and discriminant analysis do not have the same results in predicting bankruptcy in eight pharmaceutical companies because there is a miss classification in one company out of eight companies. The results of the Z-Score using discriminant analysis is able to classify a pharmaceutical company in two groups, that are healthy and gristle to bankruptcy.Keywords: pharmaceutical company, Bankruptcy Prediction, Altman Z-score model

Financial ratios and non-payment risk factor with panel probit model: a case of Turkey

ABSTRACT This study is based on the data of the companies traded on the BIST (Borsa İstanbul Stock Exchange) stock exchange with the panel probit method to obtain the risk of empirical non-payment risk with scores models. Non-Payment risk of companies will be used and compared with the Z-Score and O-Score models. In this study, the financial ratios were formed using BIST-100 data between the years January 2013 and December 2017. In the calculation of the ratios, some ratios were excluded from the analysis due to lack of data and explanation problem. The fact that the ratios do not grow is assumed to reduce the risk of non-repayment, thus causing some firms to generate a large positive number in the ratio of negative net profit and very small negative equity in their ratios and this leads to misinterpretation of the probability of non-payment. Therefore, some ratios have not been included in the analysis to eliminate this problem.

COMPARISON OF SHARIA AND CONVENTIONAL BANKING BANKRUPTCY RATES IN INDONESIA

The purpose of this study is to determine the position of financial performance, the position of bankruptcy rates of Islamic banking, as well as compare it with conventional banking. This study also compares the accuracy of the bankruptcy predictions of the Islamic banks versus conventional banks using the Altman Z-Score method with the calculation of the financial services authority (OJK). This research will be very useful to provide early warning to Islamic banking in managing the company so that the company management can create some innovations in order to develop the company, avoid bankruptcy. The analysis of this research using some methods. First, the method of Approach Regulation of the Financial Services Authority no. No. 8 / POJK.03 / 2014 which refers to Central Bank of Indonesia regulation no. 9/1 / PBI / 2007 to know the position of financial performance. Second, the Altman Z-Score model to find out the bankruptcy positions of sharia and conventional banking. This study provides the finding of the position of the financial performance level and the position of bankruptcy level of sharia and conventional banking. The conclusion of this research is the performance of sharia banking is not better than conventional banking financial performance, because the position of Islamic banking performance level is ranked 3, while conventional banking is ranked 1. The risk of bankruptcy of sharia bank CBGB 2 is in the position of the gray zone, while conventional banking CBGB 2 is in the safe zone. These results prove that both Altman Z-Score method and the method of Approach Regulation of the Financial Services Authority can provide the same prediction result.

ANALISIS PREDIKSI KEBANGKRUTAN MENGGUNAKAN MODEL ALTMAN Z- SCORE DAN ZMIJEWSKI PADA PERUSAHAAN KOSMETIK YANG TERDAFTAR DI BURSA EFEK INDONESIA

Increasingly intense competition in the cosmetics industry in Indonesia, one of which is the number of artists opening a cosmetics business and besides the entry of many cosmetics brands from abroad which makes existing cosmetic companies must be careful in running their business. This study aims to predict the bankruptcy of cosmetics companies listed on the Indonesia Stock Exchange with the Altman Z-Score model and the Zmijewski model. The sample in this study was cosmetic companies listed on the Main Board of the Indonesia Stock Exchange as many as 4 companies. The data source used is secondary data taking data from the IDX, the type of data used is quantitative data. The result of this research is bankruptcy prediction using the Altman-Z Score method showing that PT. Martino Berto, Tbk for 2016 is included in the Gray Area category while in 2017-2018 it is predicted to go bankrupt while for PT. Mustika Ratu, in 2016 - 2018 entered the Gray Area category while the other two companies namely PT. Mandom Indonesia, Tbk and PT. Unilever, Tbk from 2016 to 2018 is predicted not to go bankrupt. Meanwhile, using the Zmijewski method in cosmetics companies listed on the Indonesia Stock Exchange in the period 2016-2018 is predicted not to go bankrupt. From the comparison between the Altman Z-Score model and the Zmijewski model, the Zmijewski model has an effectiveness of 100% compared to the Altman Z-Score model which has an effectiveness level of 50%.

PENGARUH RASIO KEUANGAN TERHADAP TINGKAT KEBANGKRUTAN PERUSAHAAN MENGGUNAKAN MODEL ALTMAN Z- SCORE (Studi Empiris pada Perusahaan Real Estate dan Properti yang Terdaftar di BEI Tahun 2014 – 2016)

The purpose of this study was to determine the effect of financial ratios on bankruptcy rates using the Altman z-score model. This research was conducted on real estate and property companies on the Indonesia Stock Exchange (IDX) in 2014 - 2016. The population consists of 31 companies and a sample of 31 real estate and property companies on the Indonesia Stock Exchange (IDX). The ratio used as an analysis tool is profitability ratio, liquidity, leverage, sales growth (sales growth). The analysis technique used is multiple linear regression analysis. Data was analyzed using SPSS version 21 software. The results showed that the variables of profitability, liquidity, leverage, and sales growth had a positive and significant effect on the level of bankruptcy.

Anticipating Corporate Financial Performance from CEO Letters Utilizing Sentiment Analysis

With the emergence and tremendous growth of text mining, a computer-assisted approach for capturing sentiment viewpoints from textual data is gradually becoming a promising field, particularly when researchers are increasingly facing the problem of filtering bunches of useless information without capturing the essence in the big data era. This study aims at observing and classifying the sentiment orientation in CEO letters, digging the main corporate social responsibility (CSR) themes, and examining the effectiveness of CEO letters’ sentiment on forecasting financial performance. A specific sentiment dictionary has been proposed to identify and classify the sentiment orientation in CEO letters by utilizing the appraisal theory. Additionally, the qualitative data analysis software NVivo is applied to explore the CSR topics. Furthermore, a modified Altman’s Z-score model and machine-learning approach are employed to predict financial performance. The results of preliminary evaluations validate that approximately 62.14% of the texts represent positive polarity even when companies are not in a promising economic situation. The CSR themes mainly focus on business ethical responsibility, particularly ethical activities. Among various machine-learning approaches, the logistic regression approach is appropriate for predicting financial performance with the state-of-the-art accuracy of 70.46 %. The encouraging results indicate that the sentiment information inCEO letters is a vital factor for anticipating financial performance. This work not only offers a new analytic framework for associating linguistic theory with computer science and economic models but will also improve stakeholders’ decision-making.

Borsa İstanbul Teknoloji Endeksi (XUTEK) Şirketlerinin Altman Z-Skor Analizi İle Değerlendirilmesi

Altman Z-Skor ile finansal başarısızlık ve iflas riskini analiz etmektir. Teknoloji firmaları başlangıç ​​yatırımları ve AR-GE süreçleri arasında yoğun risk taşımaktadır. Teknoloji firmalarının bulunduğu bölgelerde sektör, çok hızlı dönüşümlerin meydana geldiği ve hızlı aksiyonlar bulunmaktadır. 16 teknoloji şirketi üzerinde gerçekleştirilmiştir. Altman Z-Skor ile ilgili finansal başarısızlık ve iflas riskini ölçümleme yapabilmek 16 teknoloji içindir ait 2019 bilanço grafikleri arasından elde edilen sonuçlar değerlendirilmiştir. Altman Z-Skoru modeli kullanılır, BİST 2019 hisse değer değişmektedir.

Refining understanding of corporate failure through a topological data analysis mapping of Altman’s Z-score model

Corporate failure resonates widely, leaving practitioners searching for understanding of default risk. Managers seek to steer away from trouble, credit providers to avoid risky loans and investors to mitigate losses. Applying Topological Data Analysis tools, this paper explores whether failing firms from the United States organise neatly along the five predictors of default proposed by the Z-score models. Each firm is represented as a point in a five-dimensional point cloud, each dimension being one of the five predictors. Visualising that cloud using Ball Mapper reveals failing firms are not always located in similar regions of the point cloud, that is they are not concentrated in an easily split out area of the space. As new modelling approaches vie to better predict firm failure, often using black boxes to deliver potentially over-fitting models, a timely reminder is sounded on the importance of evidencing the identification process. Value is added to the understanding of where in the parameter space failure occurs, and how firms might act to move away from financial distress. Further, lenders may find opportunity amongst subsets of firms that are traditionally considered to be in danger of bankruptcy, but which the Ball Mapper plots developed herein clarify actually sit in characteristic spaces where failure has not occurred.

Predicting Bankruptcy and Financial Fraud of Both Listed and Unlisted Commercial Banks in Ghana Using 3 Z-Score Models

The purpose of this study was to assess the possibilities of bankruptcy and financial statement fraud in Ghana’s banking sector. An investigation of the financial statements of the banks for the period 2015 to 2018 was made with the use of Altman’s (2000), Taffler’s (1983), and Beneish (1999) models. The Altman (2000) and Taffler (1983) models are predictors of insolvency or bankruptcy. To unveil the possibilities of financial statement fraud, this study used the Beneish [1999], model. The examination of the bank's annual financial reports with the Beneish model revealed the banks were engaged in earnings manipulation. The Altman [2000] and Taffler [1983] models, on the other hand, brought to light the financial soundness of the banks with an average of 14 (74%) and 18 (95%) of the 19 selected banks correctly classified into the safe zone with an impressive Z-Score performance according to Altman and Taffler’s models respectively. The study, therefore recommends that, if the Beneish model is applied well together with the failure prediction models by researchers, it can provide a reliable finding for policymaking. Also, auditors, investors, management, and stockholders when making good use of the Beneish model, it can provide potential ‘red flags’ for further investigation to be carried out for better audit assignment Keywords: Altman [2000] Z-score model, Beneish [1999] M-score model, bankruptcy, commercial banks, fraud, financial statement, Ghana, Taffler [1983] Z-score model . DOI: 10.7176/EJBM/12-12-05 Publication date: April 30 th 2020

MODEL PREDIKSI FINANCIAL DISTRESS : PENGARUHNYA TERHADAP KINERJA SAHAM INDUSTRI TEKSTIL DAN GARMEN DI INDONESIA

This study aims to predict the possibility of Financial distress in the textile and garment industry using the Altman Z-score prediction model and analyze the impact of Financial distress on the company's stock performance as measured by stock returns. This research used descriptive analysis and verification methods. Applying a purposive sampling method, the research sample consisted of 15 issuers from the textile and garment industry during the observation period of 2012-2016. This research used panel data regression to analyze research data. The results showed that one company did not experience financial problems, one company had potential financial problems, and the 13 other companies experienced Financial distress. The results of model testing showed that Altman Z-score can be used to predict Financial distress conditions in the textile and garment industry for the 2012-2016 period. The results of hypothesis testing showed that only one ratio of the Altman Z-score model has a significant effect on stock returns, i.e., market value of equity to book value of debt, while other ratios of working capital to total assets, retained earnings to total assets, earnings before interest and taxes to total assets, and sales to total assets have no significant effect on stock returns. These findings imply that the investors in the textile and garment industry attentively observe the company's market value in making any investment decisions.
 Keywords: Altman Z-score, Financial distress, stock returns, textile and garment industry

Z-Score Application for Jordanian Islamic Banks

This research primarily aims to utilise the Altman model of Z-score to examine the trend performance and predict bankruptcy among three Islamic banks in Jordan for the period of 2010-2016. Furthermore, it also aims to introduce the Z-score model as a beneficial diagnostic technique for possible causes standing behind the bank performance crises. The results of the Z-score model showed that the Jordan Dubai Islamic Bank (JDIB), Jordan Islamic Bank for Finance and Investment (JIBFI), and International Islamic Arabic Banks (IIAB) recorded safe zones in the period of study except for JDIB and IIAB which recorded a Grey zone in 2010, 2011, and 2012 and 2010, 2011, 2012, and 2013, respectively. The implication of this research is important to policymakers, managers, and investors who can use the information to monitor the safest bank among these three Islamic banks in Jordan based on the priority for lending that has to be done in the order of JIBFI, JDIB, and then IIAB. On the other hand, the Z-score was found to be a valid model to examine performance, and ratios utilised in computing the Z-score which was considered to provide workable instrumental indicators as well as being adopted to finance short-term and long-term projects by Jordanian Islamic banks.

Does the efficiency of corporate governance and intellectual capital affect a firm's financial distress? Evidence from Egypt

PurposeUsing data on 51 firms traded in the Egyptian Exchange from 2014 to 2016, this paper aimed to assess the efficiency of corporate governance (CG) and intellectual capital (IC) practices and to explore their influence on the probability of a firm's financial distress.Design/methodology/approachThe relative efficiency of CG and IC practices has been measured under the Malmquist data envelopment analysis model. A modified Z-score model was applied to assess firms' financial distress.FindingsThe Wilcoxon signed-rank test revealed almost insignificant evidence regarding the improvement of CG and IC efficiency over the study period. The efficiency score of CG practices had no impact on the likelihood of financial distress. However, the efficiency score of IC negatively affected the probability of financial distress.Research limitations/implicationsThe integration of data envelopment analysis with Tobit regression was required for identifying the significant drivers of efficient CG and IC.Practical implicationsThe findings shed light on the role of CG and IC in alleviating the degree of financial distress in Egypt as an emerging market, especially the need to raise firms' compliance with the Egyptian CG code from a voluntary to mandatory status.Originality/valueThis study, using Malmquist data envelopment analysis, is among the first attempts to assess the relative efficiency of CG and IC practices and their effects on financial distress.

The Comparative Analysis of Altman Z-Score, Springate, Zmijewski, And Internal Growth Rate Model in Predicting the Financial Distress (Empirical Study on Mining Companies Listed on Indonesia Stock Exchange 2014-2017)

This study aims to: (1) determine whether there are differences in scores between the Altman model, Springate, Zmijewski and Internal Growth Rate in predicting financial distress, (2) find out the most accurate prediction model in predicting financial distress of mining companies in Indonesia. The data used in this study is the company's financial statements published on Indonesia Stock Exchange. The population in this study is the mining companies listed on the Indonesia Stock Exchange during 2014-2017 which are 41 issuers. The sampling technique used purposive sampling so that 36 issuers were obtained as the research samples. This study compares the scores of four financial distress prediction models using statistical techniques and the accuracy of the prediction model by considering the level of accuracy and type I error. The conclusions from this study indicate the differences between the four prediction models. The Springate model is the best with an accuracy rate of 88.89% and an 8% type I error, the second is the Zmijewski model with an accuracy rate of 88.89% and a type I error rate of 42.86%, the third is the Altman model with 75% accuracy and error type I 46.67%, and the last is an internal growth rate model with an accuracy rate of 66.69% and type I error rate of 11.11%.Keywords: financial distress, financial statements, mining, prediction models

Pengaruh Prediksi Kebangkrutan Model Altman Z-Score, Reputasi Auditor dan Opinion Shopping terhadap Opini Audit Going Concern

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.