Forewarning Bankruptcy: An Indigenous Model for Pakistan

Ijaz, Muhammad; Hunjra, Ahmed Imran; Azam, Rauf I.

doi:10.22547/ber/9.4.12

Cited by 2 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…And financially sound companies are also expected to remain intact and growing because of stronger financial and accounting indicators. The analysis also shows that all traditional models don't yield same findings but two of these models (Z-Score and O-Score) are more robust than others (Ijaz et al, 2017). Therefore, the recommendation is to use these two models for assessing financial health of manufacturing companies and prospects.…”

Section: Conclusion Implications and Limitationsmentioning

confidence: 97%

“…The findings of both (Z-Score and Zmijewski) models were found to be consistent. Ijaz et al (2017) found that after the research of both Altman and Beaver, several other failure predictive models were also introduced by researchers. Many other scholars such as, Agarwal and Taffler (2007), Grice and Ingram (2001) and Rim and Roy (2014) used Multiple Discriminant Analysis (MDA).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Financial Distress and Forewarning Bankruptcy: An Empirical Analysis of Textile Sector in Pakistan

Rasool

Sohail

Usman

et al. 2020

RAMSS

View full text Add to dashboard Cite

This study aims to measure the financial distress and forewarn bankruptcy in Textile Sector of Pakistan using popular statistical measures i.e., Z-Score, O-Score, Probit and D-Score. First, applicable financial ratios (profitability, liquidity, leverage, market ratios) and scores (Z-Score, O-Score, Probit and D-Score) of all 77 textile companies were calculated then estimated scores were compared with cut-off point of respective model. Based on findings, models are categorized in two groups: (a) Group-I (Z-Score and O-Score), (b) Group-II (Probit and D-Score). Results indicate that some of the textile firms are about to face financial distress in near future, which could ultimately lead those firms to bankruptcy. The findings of Group-I indicate that about 43% - 44% companies in the textile sector are in the phase of financial distress; whereas the results of Group-II reveal that about 8% - 16% companies are in financial distress phase. Thus, we could draw two conclusions: (1) the two models (Z-Score and O-Score) in Group-I were found to be robust for assessing financial distress and (2) the two models (Probit and D-Score) in Group-II were found to be less rigorous in forecasting financial distress. The previous studies attempted to compare the prediction accuracy of various models by examining the data of both financially distress firms and financially stable firms. But this study is aimed to foretell bankruptcy using comprehensive models (Z-Score, O-Score, Probit and D-Score), to compare the consistency of results across all four models of the study and to categorize financially stable and financially distress companies under each model. The findings of the study are expected to be beneficial at coutry level, firm level and indiviual level such as government and regulatory bodies of Pakistan can intervene to avert bankruptcy rate, management can devise appropriate strategies to reduce financial distress. Moreover. investors can safeguard their investment by making right decissions based on the findings.

show abstract

Section: Conclusion Implications and Limitationsmentioning

confidence: 97%

Section: Literature Reviewmentioning

confidence: 99%

Financial Distress and Forewarning Bankruptcy: An Empirical Analysis of Textile Sector in Pakistan

Rasool

Sohail

Usman

et al. 2020

RAMSS

View full text Add to dashboard Cite

show abstract

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

Thinh

Tuan

Huy³

et al. 2020

Investment Management and Financial Innovations

View full text Add to dashboard Cite

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.

show abstract

Forewarning Bankruptcy: An Indigenous Model for Pakistan

Abstract: Abstract

Cited by 2 publications

References 14 publications

Financial Distress and Forewarning Bankruptcy: An Empirical Analysis of Textile Sector in Pakistan

Financial Distress and Forewarning Bankruptcy: An Empirical Analysis of Textile Sector in Pakistan

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

Contact Info

Product

Resources

About