Industry specific financial distress modeling

Sayari, Naz; Mugan, Can Simga

doi:10.1016/j.brq.2016.03.003

Cited by 52 publications

(41 citation statements)

References 48 publications

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“…In addition to accounting ratios, market variables are also used in an ex-ante model as they contain information on expected future cash flows, which are relevant to the likelihood of being financial distressed (Rees, 1995 A literature review shows that there is a great number of predictors that can be utilized in a financial distress prediction model. According to Zhou et al (2012), there are 500 different variables that can be found in 128 papers and the predictive power of each variable changes in different papers (Sayari & Mugan, 2016). As stated by Powell (2007), the high dimensionality problem can be raised if too many variables are used for data analysis.…”

Section: Review Of Predictors and Predictor Selectionmentioning

confidence: 99%

Feature selection methods and sampling techniques to financial distress prediction for Vietnamese listed companies

Vu¹,

Vu²,

Nguyen

et al. 2019

Investment Management and Financial Innovations

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The research is taken to integrate the effects of variable selection approaches, as well as sampling techniques, to the performance of a model to predict the financial distress for companies whose stocks are traded on securities exchanges of Vietnam. A firm is financially distressed when its stocks are delisted as requirement from Vietnam Stock Exchange because of making a loss in 3 consecutive years or having accumulated a loss greater than the company’s equity. There are 12 models, constructed differently in feature selection methods, sampling techniques, and classifiers. The feature selection methods are factor analysis and F-score selection, while 3 sets of data samples are chosen by choice-based method with different percentages of financially distressed firms. In terms of classifying technique, logistic regression together with SVM are used in these models. Data are collected from listed firms in Vietnam from 2009 to 2017 for 1, 2 and 3 years before the announcement of their delisting requirement. The experiment’s results highlight the outperformance of the SVM model with F-score selection method in a data sample containing the highest percentage of non-financially distressed firms.

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Section: Review Of Predictors and Predictor Selectionmentioning

confidence: 99%

Feature selection methods and sampling techniques to financial distress prediction for Vietnamese listed companies

Vu¹,

Vu²,

Nguyen

et al. 2019

Investment Management and Financial Innovations

View full text Add to dashboard Cite

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“…Ohlson (1980) derives a bankruptcy prediction model as an alternative to Altman' s Z score model. The study employs logistic regression to examine the probability of a firm being bankrupt or non-bankrupt for the period of 1970 -1976 (Sayari, Naz and Can Simga Mugan, 2017). The Ohlson model is different from the previous study model because this model has 9 variables consisting of several financial ratios.…”

Section: Ohlson' S Modelmentioning

confidence: 99%

Comparison of Bankruptcy Prediction Models Analysis (Altman, Springate, Grover, Ohlson and Zmijewski) on Pt. Asuransi Harta Aman Pratama, Tbk.

Putri

2018

EAJ (Economic and Accounting Journal)

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PT. Asuransi Harta Aman Pratama, Tbk. is a financial services company which is specialized in general insurance. This research is conducted based on five annual reports spanned from 2012 to 2016 which are independently audited. This study, therefore, aims to compare with five models bankruptcy predictions; the Altman, Springate, Grover, Ohlson and Zmijewski. This study uses a quantitative research approach, using the financial statements data of PT. Asuransi Harta Aman Pratama, Tbk. which also has been published in BEI. This paper analyze the prediction of every method using analysis of variance. The result of this analysis show the differences between the applied models.

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“…Dengan mengunakan model ini, maka gejal satau ancaman kesulitan keuangan secara dini dapat diketahui sehingga dapat dilakukan upaya-upaya perbaikan sebelum kondisi perusahaan berada dalam kondisi krisis. (Sayari & Simga, 2017).…”

Section: Pendahuluanunclassified

Analisis Penilaian Financial Distress Menggunakan Model Altman (Z-Score) Perusahaan Manufaktur

Hikmah

Afridola

2018

niara

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The most significant industrial development in Batam City in recent years, this is done with go public and private companies that have gone bankrupt and observe bankruptcy. PT Citra Tubindo and PT Sat Nusapersada, Tbk are one of the manufacturing companies listed on the IDX that provide influence in the city of Batam, which caused a decline in financial and financial performance. This study aims to Distress finance at the company PT Citra Tubindo and PT Sat NusaPersada, Tbk using the Altman Z-Score method. This method uses financial statements to be processed using variables from Z-Score. The analysis technique used is the Altman Zscore bankruptcy score model. By using variables that represent liquidity (X1), profitability (X2) and (X3), activity (X4) and (X5). The results of the study indicate that PT Citra Tubindo has a Z-score value in 2015 and 2017 covering bankruptcy. In 2016, bankruptcy references need to be done by increasing financial ratios, profitability and activities. Whereas for PT Sat Nusapersada, Tbk in 2015and 2016 healthy, in 2017 the company is prone to vulnerability. AbstrakPerkembangan industri di Kota Batam mengalami penurunan yang signifikan beberapa tahun terakhir, hal ini terlihat dengan banyaknya perusahaan go public dan privat yang telah bangkrut dan berpotensi bangkrut.. PT Citra Tubindo dan PT Sat Nusapersada, Tbk adalah salah satu perusahaan manufaktur yang yang terdaftar di BEI yang terkena dampak dari perkembangan perekonomian di Kota Batam, yang menyebabakan terjadinya penurunan kinerja keuangan dan financial distress. Penelitian ini bertujuan untuk penilaian financial Distress pada perusahaan PT Citra Tubindo dan PT Sat NusaPersada, Tbk dengan menggunakan metode Altman Z-Score. Metode ini menggunakan laporan keuangan untuk di analisis dengan menggunakan variabel dari Z-Score. Teknik analisis yang digunakan adalah model prediksi kebangkrutan Altman Z-score. Dengan menggunakan lima variabel yang mewakili rasio likuiditas (X 1 ), profitabilitas (X 2 ) dan (X 3 ), aktivitas (X 4 ) dan (X 5 ). Hasil penelitian menunjukkan bahwa PT Citra Tubindo memiliki nilai Z-score pada tahun 2015 dan tahun 2017 berpotensi bangkrut,. Sedangkan pada tahun 2016 berpotensi rawan bangkrut sehingga perlu melakukan perbaikan dengan meningkatkan rasio keuangan likuiditas, profitabilitas dan aktivitas. Sedangkan untuk PT Sat Nusapersada, Tbk pada tahun 2015 dan 2016 sehat, sedangkan pada tahun 2017 perusahaan berpotensi rawan. . Kata Kunci : Financial Distress, Altman's Z-Score, Perusahaan Manufaktur.

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Industry specific financial distress modeling

Cited by 52 publications

References 48 publications

Feature selection methods and sampling techniques to financial distress prediction for Vietnamese listed companies

Feature selection methods and sampling techniques to financial distress prediction for Vietnamese listed companies

Comparison of Bankruptcy Prediction Models Analysis (Altman, Springate, Grover, Ohlson and Zmijewski) on Pt. Asuransi Harta Aman Pratama, Tbk.

Analisis Penilaian Financial Distress Menggunakan Model Altman (Z-Score) Perusahaan Manufaktur

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