Modeling Bankruptcy Prediction for Non-Financial Firms: The Case of Pakistan

Abbas, Qaiser; Rashid, Abdul

doi:10.2139/ssrn.1917458

Cited by 11 publications

(14 citation statements)

References 17 publications

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“…But in 2008, 2011and 2012 that are not significant. There exists significant positive correlation between the Altman"s Z-Score and current Abbas model in 2007 to 2012.…”

Section: Discussionmentioning

confidence: 77%

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Bankruptcy Prediction for Non-Financial Firms of Pakistan

Roomi

Ahmad

Ramzan

et al. 2015

ijafr

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In this study we use two models for the measuring of financial status of the non-financial firms which are listed in the Karachi Stock Exchange. The Non-financial companies represent the biggest slice at the Karachi Stock Exchange. The non-financial companies of Pakistan are the total population and sample size is 25 higher and 25 lower capital companies. The ISSN 2162-3082 2015 www.macrothink.org/ijafr 27 technique which used in this study was Convenience sampling technique and all 50 non-financial listed companies at KSE were included to gain deeper insights into this study. The State Bank of Pakistan shows balance sheet analyses of companies, for compiling of data financial reports were used for the years 2007 to 2012. The results of the study showed that Abbas model and Altman"s Z-Score model was a effective tool for checking the financial health of non-financial companies listed at Karachi stock exchange. This study further explores that lower capital firm have more financially distressed companies as compare to high capital non-financial companies listed at KSE. International Journal of Accounting and Financial Reporting

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“…But in 2008, 2011and 2012 that are not significant. There exists significant positive correlation between the Altman"s Z-Score and current Abbas model in 2007 to 2012.…”

Section: Discussionmentioning

confidence: 77%

“…The bankruptcy prediction has high predictive ability through the study of MDA. Abbas and Rashid (2011) model use for testing because they test model and predict bankruptcy in Pakistan. The dependent variable of these models predicts the insolvency possibility of the company in year.…”

Section: Data Analysis Modelsmentioning

confidence: 99%

Bankruptcy Prediction for Non-Financial Firms of Pakistan

Roomi

Ahmad

Ramzan

et al. 2015

ijafr

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“…There are only a few studies that have explored the financial vulnerability of the firms in the context of Pakistan but they are mainly concerned with non-financial sectors. The previous research of Abbas and Rashid [5] employed multiple discriminant analysis (MDA) for the non-financial sector of Pakistan and achieved 76.9% prediction accuracy. Mehta [13] conducted a study for assessing the financial position of textile sector.…”

Section: Bankruptcy Prediction For Financial Sector Of Pakistan: Evaluation Of Logit and Discriminant Analysis Approachesmentioning

confidence: 99%

“…Extensive work has been done in this area and there are several models proposed by various studies of bankruptcy. Abbas and Rashid [5] obtained 76.9% accuracy by using MDA while Mehta [13] found 92% accuracy of logit model when applied to textile sector of Pakistan. This study models financial distress by using both MDA and logit model for the financial sector of Pakistan aimed to identify the model with higher rate of classification.…”

Section: B Data Analysis Modelsmentioning

confidence: 99%

Bankruptcy Prediction for Financial Sector of Pakistan: Evaluation of Logit and Discriminant Analysis Approaches

Khan¹

2018

Pakistan Journal of Engineering, Technology & Science

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<p>Bankruptcy prediction is one of the core area in finance that is quite rich in empirical and theoretical work. This study compares two models for measuring the financial position of financial firms listed in Karachi Stock Exchange. The study gives a comprehensive review of two models, namely Altman’s [1] Z-score and an O-Score derived from Ohlson [14]. The purpose of this paper is two folded. First to identify unique characteristics of business failure and to compare effective variables responsible for this response. Secondly to compare two popular accounting-based measures. summarize publiclyavailable information about bankruptcy. The sample period for this study is from 2009 to 2015. From the KSE listed financial firms, a total of 40 firms were selected and accounting ratios were extracted from balance sheet analysis reports published by State bank of Pakistan. The empirical results concluded that the logit model has a high rate of classification as compared to multiple discriminant analysis. The model has obtained overall 85.5% accuracy and identified three significant accounting ratios that are: retained earnings to total asset, earnings before income and taxes to the total asset, and current liabilities to total asset. The finding of this study would benefit stakeholders that are affected by bankruptcies. So in order to take an advantage, it is important to understand the phenomenon that causes bankruptcies.</p>

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“…2 Ijaz et al (2013) report that the number of business failures in Pakistan is increasing, which requires immediate attention of the government. Newton (1985) as cited in Abbas and Ahmad (2011), report that one of the main reasons behind varying corporate failure rates in different countries is the difference in the capital structure of the businesses. Bankruptcy due to use of the high debt may be explained in context of trade-off theory of the capital structure (Matemilola et al, 2013).…”

Section: Introductionmentioning

confidence: 99%