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Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud

This study investigates the usefulness of financial ratio in predicting the financial distress of companies in Malaysia. 67 companies were analyzed with 11 initial financial ratios that have been grouped to five categories. They are firm size, cash flow, efficiency ratio, profitability ratio and li...

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Bibliographic Details
Main Author: Daud, Farhana
Format: Student Project
Language:English
Published: 2013
Subjects:
Banking
Bank reserves. Bank liquidity. Loan loss reserves
Liquidity
Online Access:http://ir.uitm.edu.my/id/eprint/41086/1/41086.pdf
http://ir.uitm.edu.my/id/eprint/41086/
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spelling my.uitm.ir.410862021-01-26T07:57:07Z http://ir.uitm.edu.my/id/eprint/41086/ Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud Daud, Farhana Banking Bank reserves. Bank liquidity. Loan loss reserves Liquidity This study investigates the usefulness of financial ratio in predicting the financial distress of companies in Malaysia. 67 companies were analyzed with 11 initial financial ratios that have been grouped to five categories. They are firm size, cash flow, efficiency ratio, profitability ratio and liquidity ratio. From 67 companies, we take 40 of non-distress companies and 27 of distress companies. These 27 distress companies have obtained court protection against their creditors under Section 176 of the Malaysian Companies Act, 1965. Most of the analysis of data found that the overall variable is found significant. But, the findings revealed that financial ratios that measure liquidity are the most significant in their discriminating power on whether a company is successful or will become financially distressed. It is match with the theory where liquidity ratios determine company’s ability to pay short term debt obligation, thus the larger margin of safety that company possesses to cover its short-term debts. From the predictive ability of the model, the overall classification rate is 82.1 percent. This overall study showed the result is quite good, but to increase the accuracy more ratios need to be added. With more advanced statistical models used recently, logistic regression (Logit Model) is still effective and reliable statistical tool. This study will provide a better understanding on the relevant factors that lead to corporate distress and can take the immediate action to minimize the risk 2013-01 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/41086/1/41086.pdf Daud, Farhana (2013) Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud. [Student Project] (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Banking
Bank reserves. Bank liquidity. Loan loss reserves
Liquidity
spellingShingle Banking
Bank reserves. Bank liquidity. Loan loss reserves
Liquidity
Daud, Farhana
Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
description This study investigates the usefulness of financial ratio in predicting the financial distress of companies in Malaysia. 67 companies were analyzed with 11 initial financial ratios that have been grouped to five categories. They are firm size, cash flow, efficiency ratio, profitability ratio and liquidity ratio. From 67 companies, we take 40 of non-distress companies and 27 of distress companies. These 27 distress companies have obtained court protection against their creditors under Section 176 of the Malaysian Companies Act, 1965. Most of the analysis of data found that the overall variable is found significant. But, the findings revealed that financial ratios that measure liquidity are the most significant in their discriminating power on whether a company is successful or will become financially distressed. It is match with the theory where liquidity ratios determine company’s ability to pay short term debt obligation, thus the larger margin of safety that company possesses to cover its short-term debts. From the predictive ability of the model, the overall classification rate is 82.1 percent. This overall study showed the result is quite good, but to increase the accuracy more ratios need to be added. With more advanced statistical models used recently, logistic regression (Logit Model) is still effective and reliable statistical tool. This study will provide a better understanding on the relevant factors that lead to corporate distress and can take the immediate action to minimize the risk
format Student Project
author Daud, Farhana
author_facet Daud, Farhana
author_sort Daud, Farhana
title Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
title_short Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
title_full Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
title_fullStr Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
title_full_unstemmed Predicting corporate financial distress using the logit model: Case in Malaysia / Farhana Daud
title_sort predicting corporate financial distress using the logit model: case in malaysia / farhana daud
publishDate 2013
url http://ir.uitm.edu.my/id/eprint/41086/1/41086.pdf
http://ir.uitm.edu.my/id/eprint/41086/
_version_ 1690374307650207744
score 13.211869

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