An Analysis of Assessment of Financial Distress in Textile Sector of Pakistan (2012-2018)

Khan, Talha Majeed

doi:10.7176/ejbm/11-19-01

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…The increase in the TATO ratio shows that the more efficient the company is in managing its assets so that it is increasingly protected from financial difficulties. This is supported by the results of research by Santosa et al (2020), Ramadhan (2021), Khan (2019) which found that activities have a significant negative effect on financial distress. H4: activities have a negative influence on financial distress.…”

Section: The Effect Of Activities On Financial Distressmentioning

confidence: 53%

“…The more ROA increases, the better the company's condition so that it is increasingly protected from financial distress. The results of research by Nurhamidah (2021), Handayani (2020), Rudiyanto (2021), Mahaningrum (2020), Ramadhan (2021), Dwiantari (2021), Isayas (2021), Khan (2019), Kamaluddin (2019), Balasubramanian (2019) and Waqas (2018) found that profitability has a significant negative effect on financial distress. H1: profitability negatively affects Financial Distress.…”

Section: Research Hipotesis the Effect Of Profitability On Financial ...mentioning

confidence: 99%

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The Influence of Financial Performance and Macroeconomic Factors on the Financial Distress of Textile and Garment Companies Listed on the Stock Exchange: Empirical Studies in Indonesia

Arianto,

Kurniasih

2023

JEFMS

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This study aims to determine the influence of financial performance factors and macroeconomic factors on financial distress in textile and garment companies in Indonesia. In this study, quantitative methods were used with causality research design. The study population is textile and garment companies listed on the Indonesia Stock Exchange in 2022. The research sample consisted of textile and garment sub-sector companies listed on the IDX for 5 consecutive years (2017-2021) and had audited financial statements. Companies that meet the sample criteria are 16 companies. Descriptive and inferential analyses are performed on the data. In inferential analysis, a panel data regression approach is used. The results showed that of the 9 research variables, there were 3 variables that had a significant influence on financial distress. Liquidity (CR) has a significant negative influence, Leverage (DAR) has a significant positive influence, and Activity (TATO) has a significant negative influence. Other variables such as profitability, sales growth, interest rates (BI 7day repo rate), exchange rates, world cotton prices (cotlook A index) and economic growth (GDP) do not affect financial distress.

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Section: The Effect Of Activities On Financial Distressmentioning

confidence: 53%

Section: Research Hipotesis the Effect Of Profitability On Financial ...mentioning

confidence: 99%

The Influence of Financial Performance and Macroeconomic Factors on the Financial Distress of Textile and Garment Companies Listed on the Stock Exchange: Empirical Studies in Indonesia

Arianto,

Kurniasih

2023

JEFMS

View full text Add to dashboard Cite

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

Rasool

Sohail

Usman

et al. 2020

RAMSS

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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.

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An Analysis of Assessment of Financial Distress in Textile Sector of Pakistan (2012-2018)

Cited by 2 publications

References 12 publications

The Influence of Financial Performance and Macroeconomic Factors on the Financial Distress of Textile and Garment Companies Listed on the Stock Exchange: Empirical Studies in Indonesia

The Influence of Financial Performance and Macroeconomic Factors on the Financial Distress of Textile and Garment Companies Listed on the Stock Exchange: Empirical Studies in Indonesia

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

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