scholarly journals Financial Distress Prediction of Airlines Companies

2021 ◽  
Vol 5 (2) ◽  
pp. 3-15
Author(s):  
Afiruddin Tapa ◽  
Nurfarah Lyana Ahmad Razif
Keyword(s):  
Middle East ◽  
Financial Distress ◽  
Descriptive Analysis ◽  
Z Score ◽  
Financial Distress Prediction ◽  
Financial Failure ◽  
Significant Difference ◽  
Distress Prediction ◽  
Score Model ◽  
Significant Model

The purpose of this study is to compare three financial failure models: the Altman Z-Score Model, the Springate Model, and the Zmijewski Model, in terms of predicting financial difficulty among airlines in Asia and the Middle East. Based on the results of this study, it is proven by the result of the analysis done for Airlines in Asia and the Middle East that all the three models have predicted that these companies are in financial distress. But, the Altman Z-Score model is the most significant model to forecast financial distress. Although the models employ different ratios in their analyses, this study demonstrates that there is a substantial difference in the analysis of these three models. Another independent T-test demonstrates that the Altman Z-Score Model and the Zmijewski Model, as well as the Springate Model and the Zmijewski Model, have substantial differences. The study employed a descriptive and comparative analysis method, and this model was created to compare the independent variables. The Altman Z-Score model is the most significant model for predicting the financial failure of enterprises, according to the descriptive analysis in this study. While the comparison findings show a large difference between the Altman Z-Score Model and the Zmijewski Model, there is also a significant difference between the Springate Model and the Zmijewski Model. The Altman Z-Score Model and the Springate Model, on the other hand, imply that there is no significant model.

FINANCIAL DISTRESS PREDICTION AND SEEING THE INFLUENCE OF THE ALTMAN RATIO ON COMPANY FINANCIAL DISTRESS

2018 ◽  
Vol 23 (3) ◽  
pp. 236-243
Author(s):  
Hadhi Dharmaputra Juliyan ◽  
Bertilia Lina Kusrina
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Large Role ◽  
Corporate Bankruptcy ◽  
Mining Companies ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Score Model

This research aims to determine the level of the bankruptcy of the company and to see if the Altman ratio can predict the condition of corporate bankruptcy in mining companies on the Indonesia Stock Exchange because mining companies have a large role in the Indonesian economy. This study uses the Altman Z-Score model analysis to see how much the company's bankruptcy prediction and uses logistic regression to see how much the influence of the Altman ratio in predicting corporate bankruptcy. Keywords: financial distress, the Altman z–score, bankruptcy prediction

scholarly journals Does audit report information improve financial distress prediction over Altman's traditional Z ‐Score model?

2019 ◽  
Vol 31 (1) ◽  
pp. 65-97
Author(s):  
Nora Muñoz‐Izquierdo ◽  
Erkki K. Laitinen ◽  
María‐del‐Mar Camacho‐Miñano ◽  
David Pascual‐Ezama
Keyword(s):  
Financial Distress ◽  
Z Score ◽  
Audit Report ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Score Model

scholarly journals Financial distress prediction of listed companies – empirical evidence on the Vietnamese stock market

2020 ◽  
Vol 17 (2) ◽  
pp. 377-388
Author(s):  
Tran Quoc Thinh ◽  
Dang Anh Tuan ◽  
Nguyen Thanh Huy ◽  
Tran Ngoc Anh Thu
Keyword(s):  
Stock Market ◽  
Financial Distress ◽  
Financial Statements ◽  
Listed Companies ◽  
Research Model ◽  
Z Score ◽  
Economic Decisions ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
High Level

Financial distress is a matter of concern in the recent period as Vietnam gradually enters global markets. This paper aims to examine the factors of Altman Z-score to detect the financial distress of Vietnamese listed companies. The authors use a sample of 30 delisted companies due to financial problems and 30 listed companies on the Vietnamese stock market from 2015 to 2018. They employ Independence Samples T-test to test the research model. It is found that there are significant differences in the factors of Altman Z-score between the group of listed companies and the group of delisted companies. Further analyses using subsamples of delisted companies show that the factors of Altman Z-score are also statistically different between companies with a low level of financial distress and those with a high level of financial distress. Based on the results, there are some suggestions to assist practitioners and the State Securities Commission in detecting, preventing, and strictly controlling financially distressed businesses. These results also enable users of financial statements to make more rational economic decisions accordingly.

scholarly journals PREDIKSI FINANCIAL DISTRESS BERDASARKAN VARIABEL-VARIABEL KEUANGAN PADA INDUSTRI TEKSTIL

2018 ◽  
Vol 4 (1) ◽  
pp. 54-60
Author(s):  
REFNI SUKMADEWI
Keyword(s):  
Prediction Model ◽  
Financial Distress ◽  
Z Score ◽  
Financial Distress Prediction ◽  
Distress Prediction

Penelitian ini bertujuan untuk memberikan bukti empiris mengenai faktor-faktor yang mempengaruhi financial distress perusahaan. Penelitian ini menguji peran rasio keuangan dalam memprediksi terjadinya financial distress pada perusahaan industri tekstil yang tercatat di Bursa Efek Jakarta. Analisis diskriminan digunakan untuk menguji kemampuan rasio keuangan untuk memprediksi financial distress dan membangun model prediksi distress financial dengan menggunakan prosedur stepwise. Variabel indikator adalah rasio keuangan. Hasil penelitian menunjukkan bahwa ada empat rasio yang berbeda dan secara signifikan mempengaruhi model prediksi distress keuangan. Rasio tersebut adalah Rasio Aktiva Lancar / Kewajiban Lancar, Modal Kerja / Jumlah Aktiva, Pendapatan Bersih / Total Aktiva, Kewajiban / Total Aset. Hasil klasifikasi berdasarkan nilai cut-off-Z Score mampu memprediksi kesulitan finansial perusahaan pada industri tekstil dengan tingkat akurasi 0f 100%. Tingkat akurasi model menunjukkan bahwa model diskriminan akurat dalam mengukur tekanan keuangan pada perusahaan industri tekstil. Kata kunci: Financial distress, Prediction Model, Rasio Keuangan

scholarly journals Analysis on the Performance of Technology Companies with Z-score Model

2018 ◽  
Vol 7 (4) ◽  
pp. 633-639
Author(s):  
Lam Weng Hoe ◽  
Yeoh Hong Beng ◽  
Lam Weng Siew ◽  
Chen Jia Wai
Keyword(s):  
Organizational Performance ◽  
Financial Distress ◽  
Dominant Factor ◽  
Z Score ◽  
Financial Ratio ◽  
Technology Sector ◽  
Financial Failure ◽  
Distress Level ◽  
Information And Communication ◽  
Score Model

Local technology sector plays a significant role in information and communication technology (ICT) based innovations and applications which enhance organizational performance as well as national economic growth and labor productivity. In this paper, financial performance of the listed Malaysia companies in technology sector is analyzed and evaluated. Altman’s Z-score model is proposed due to its robustness in determining companies’ financial distress level using five financial ratios as variables. The computed Z-score values classify the financial status of the companies into distress, grey and safe zones. This study investigates the financial data of 23 listed technology-based companies in the Main Market of Bursa Malaysia over the period of 2013 to 2017. The findings reveal that the percentage of safe zone companies increase throughout the five years whereas distress zone companies decline. It is concluded that financial ratio for market value of equity to total liabilities is the dominant factor that directly influences the level of financial distress among these technology-based companies in Malaysia. These research outcomes provide an insight to investors or policy makers to develop future planning in order to avoid financial failure in local technology sector.

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