A study of financial distress prediction on nonfinancial sector in Pakistan
Financial distress has become an eye-catching issue among the researchers. As the number of companies filling for bankruptcies in Pakistan are increasing due to the uncertainty of the economy. A specific model is needed in helping companies to identify significant predictors of financial distress. T...
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Format: | Thesis |
Language: | eng eng eng |
Published: |
2021
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Online Access: | https://etd.uum.edu.my/10299/1/Permission%20to%20deposit_s900671.pdf https://etd.uum.edu.my/10299/2/s900671_01.pdf https://etd.uum.edu.my/10299/3/s900671_02.pdf |
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Summary: | Financial distress has become an eye-catching issue among the researchers. As the number of companies filling for bankruptcies in Pakistan are increasing due to the uncertainty of the economy. A specific model is needed in helping companies to identify significant predictors of financial distress. This study intends to analyze the financial distress scenario of non-financial companies listed in the Pakistan Stock Exchange for the period of 2005 to 2016. Various financial ratios were identified which can predict financial distress in the Pakistani companies. In this study, the Principal Component Analysis (PCA) and Logit were utilized in predicting financial distress using individual financial ratio and financial ratios indices. A total of 23 financial ratios was divided into six main categories which are profitability, liquidity, leverage, asset efficiency, size and growth. Results indicate that the financial ratio indices are better in predicting financial distress as compared to the individual ratios with precision models. Also, the accuracy rates prior to bankruptcy are 93.90 percent for the first year followed by 81.93 percent, 78.67 percent, 75.71 percent and 73.71 percent for the second, third, fourth and fifth year, respectively. The accuracy rates of individual financial ratios are generally less than the financial ratio indices in all five years period. The results also indicate that all financial ratio categories are significantly predict the financial distress of a company. The model developed from this study is useful for policymakers at securities and exchange commission, State Bank of Pakistan, commercial banks, and investors. Being an indigenous model, it can capture more accounting information and has practical application in predicting financial distress in Pakistan. |
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