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 ANALISIS PERBANDINGAN METODE ALTMAN Z-SCORE DAN METODE SPRINGATE SCORE DALAM MENENTUKAN FINANCIAL DISTRESS PADA PERUSAHAAN ASURANSI JIWA SYARIAH TAHUN 2014-2018

2020 ◽  
Vol 7 (12) ◽  
pp. 2494
Author(s):  
Iif Maulidya ◽  
Dian Filianti
Keyword(s):  
Life Insurance ◽  
Financial Distress ◽  
Financial Statements ◽  
Insurance Companies ◽  
Z Score ◽  
Marine Life ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Score Method ◽  
Method Show

ABSTRAKTujuan penelitian ini adalah untuk mengetahui dan menganalisis prediksi financial distress pada perusahaan asuransi jiwa syariah dari tahun 2014 hingga 2018 dengan menggunakan metode Altman Z-Score dan Springate S-Score. Penelitian ini menggunakan data sekunder yaitu laporan keuangan tahunan perusahaan asuransi jiwa syariah periode 2014-2018. Metode pengumpulan data yang digunakan adalah metode dokumentasi dengan menggunakan studi pustaka. Studi literatur ini dilakukan dengan mengambil informasi secara tidak langsung terkait dengan laporan keuangan dan profil lengkap perusahaan asuransi yaitu melalui situs resmi perusahaan asuransi jiwa syariah dan Otoritas Jasa Keuangan (OJK). Hasil akhir penelitian ini menunjukkan bahwa kinerja keuangan yang dianalisis dengan metode Altman Z-Score dan Springate S-Score pada perusahaan asuransi jiwa syariah periode 2014-2018 tergolong dalam keadaan financial distress. Hasil prediksi financial distress dengan menggunakan metode Altman Z-Score menunjukkan tiga perusahaan mengalami financial distress yaitu PT. Bringin Jiwa Sejahtera, Asuransi Jiwa, PT. Tokio Marine Life Insurance Indonesia, PT. Asuransi Jiwa Asia Tengah Raya. Hasil prediksi financial distress dengan metode Springate S-Score menunjukkan lima perusahaan mengalami financial distress yaitu PT. Asuransi Jiwa Tokio Marine, PT. Panin Daichi Life, PT. Bringin Jiwa Sejahtera, Asuransi Jiwa, PT. Asuransi Jiwa Bringin Jiwa Sejahtera, dan PT. Asuransi Jiwa Asia Tengah Raya.Kata kunci: financial distress, metode Altman Z-Score, metode Springate S-Score ABSTRACTThe purpose of this study was to determine and analyze the prediction of financial distress in Islamic life insurance companies from 2014 to 2018 using the Altman Z-Score and Springate S-Score methods. This study uses secondary data, namely the annual financial statements of Islamic life insurance companies for the 2014-2018 period. The data collection method used is the documentation method using literature studies. This literature study was carried out by taking information indirectly related to financial statements and complete profiles of insurance companies, namely through the official website of the Islamic life insurance company and the Financial Services Authority (OJK). The final results of this study indicate that the financial performance analyzed by the Altman Z-Score and Springate S-Score methods in Islamic life insurance companies in the 2014-2018 period was classified as being in a state of financial distress. The results of financial distress prediction using the Altman Z-Score method show that three companies experience financial distress, namely PT. Bringin Jiwa Sejahtera, Life Insurance, PT. Tokio Marine Life Insurance Indonesia, PT. Central Asia Life Insurance Raya. The results of financial distress prediction using the Springate S-Score method show that five companies experience financial distress, namely PT. Tokio Marine Life Insurance, PT. Panin Daichi Life, PT. Bringin Jiwa Sejahtera, Life Insurance, PT. Bringin Jiwa Sejahtera Life Insurance, and PT. Central Asia Life Insurance Raya.Keywords: financial distress, Altman Z-Score method, Springate S-Score method

scholarly journals Post COVID-19 Financial Distress: Prediction of Corporate Defaults at Pakistan Stock Exchange (PSX)

2021 ◽  
Vol 5 (1) ◽  
pp. 286-400
Author(s):  
Khalid Mumtaz Khan ◽  
Naeem Ullah
Keyword(s):  
Financial Markets ◽  
Financial Distress ◽  
Stock Exchange ◽  
Economic Recession ◽  
Financial Statements ◽  
Future Research ◽  
Z Score ◽  
Corporate Default ◽  
Financial Distress Prediction ◽  
Distress Prediction

COVID-19 has slowed down the global economic activity which is expected to turn into an economic recession, where firms are expected to experience financial distress leading to corporate defaults. Predicting such defaults is important to safeguard stakeholders’ interest in financial markets. This study has estimated extent of financial distress among firms listed at PSX and constituting KSE 30 index, by using Altman’s Z-Score. The score has been computed using financial statements of 2019-20, and on proforma financial statements for 2020-21 2019-20, considering these financial years as pre and post COVID-19 closing dates respectively for financial statements. The proforma financial statements have been drawn for financial 2020-21 2019-20 using established accounting conventions of prudence, conservatism, substance over form, ad foreseeable future. The results of Z-score in pre and post COVID-19 have been compared to assess the change in degree of financial distress among the selected firms. A significant increase in the degree of financial distress has been observed, which may lead to an increased number corporate default for the firms listed at PSX. Suggestion have been made to the firms and corporate regulators to curtail the rate of corporate defaults, along with limitation of this study and areas of future research.

PREDICTING FINANCIAL DISTRESS OF CHINESE LISTED COMPANIES USING ROUGH SET THEORY AND SUPPORT VECTOR MACHINE

2011 ◽  
Vol 28 (01) ◽  
pp. 95-109 ◽  
Author(s):  
YU CAO ◽  
GUANGYU WAN ◽  
FUQIANG WANG
Keyword(s):  
Support Vector Machine ◽  
Set Theory ◽  
Rough Set ◽  
Financial Distress ◽  
Rough Set Theory ◽  
Listed Companies ◽  
Support Vector ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Chinese Listed Companies

Effectively predicting corporate financial distress is an important and challenging issue for companies. The research aims at predicting financial distress using the integrated model of rough set theory (RST) and support vector machine (SVM), in order to find a better early warning method and enhance the prediction accuracy. After several comparative experiments with the dataset of Chinese listed companies, rough set theory is proved to be an effective approach for reducing redundant information. Our results indicate that the SVM performs better than the BPNN when they are used for corporate financial distress prediction.

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