Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia

Investors need to understand the background of the business before they started to invest in the stock market. Good business management can help the business to perform better. Each of the businesses leads to a different result this is based on the business management decision making as well as the...

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Main Author:	Ong, Gek Hwa
Format:	Thesis
Language:	eng eng
Published:	2021
Subjects:	HG Finance
Online Access:	https://etd.uum.edu.my/11142/1/s826698_01.pdf https://etd.uum.edu.my/11142/2/s826698_02.pdf
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id	my-uum-etd.11142
record_format	uketd_dc
spelling	my-uum-etd.111422024-06-10T01:49:02Z Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia 2021 Ong, Gek Hwa Tapa, Afiruddin School of Economics, Finance & Banking School of Economics, Finance & Banking HG Finance Investors need to understand the background of the business before they started to invest in the stock market. Good business management can help the business to perform better. Each of the businesses leads to a different result this is based on the business management decision making as well as the business process flow. Investors have to understand the business type and the function of each business carefully to avoid misallocation of their funds. Business when into financial bankruptcy when the business debts are higher than assets there will be total bankruptcy which the business falls into bankruptcy and legal steps are taking place to ensure creditors or liquidation occurs. This is to ensure that the investment plan can make a profit for investors rather than making a loss. The value of the investment affected the confidence level of the investors by putting in their funds in the stock market. Prediction makes formerly is to prevent a business from sudden fall into bankruptcy. Altman Z-score and Logit model are implemented to predict the chance of bankruptcy. 40 companies were taken for prediction, 20 out of 40 companies are financial distress companies and the other 20 companies are non-financial distress companies. This paper is to help investors to have a good analysis for their investment decision. Logit model shows that the result from the calculation probability which is more than 0.5 as financial distress, less than 0.5 consider as non-financial distress, and showed that the result is predicted 92% of the analyses. The results show that there is a significant 5% level are sales to total assets, shareholders’ fund to total liabilities, cash from operating to total liabilities in the logit model for prediction. 2021 Thesis https://etd.uum.edu.my/11142/ https://etd.uum.edu.my/11142/1/s826698_01.pdf text eng 2024-08-11 staffonly https://etd.uum.edu.my/11142/2/s826698_02.pdf text eng public other masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Tapa, Afiruddin
topic	HG Finance
spellingShingle	HG Finance Ong, Gek Hwa Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
description	Investors need to understand the background of the business before they started to invest in the stock market. Good business management can help the business to perform better. Each of the businesses leads to a different result this is based on the business management decision making as well as the business process flow. Investors have to understand the business type and the function of each business carefully to avoid misallocation of their funds. Business when into financial bankruptcy when the business debts are higher than assets there will be total bankruptcy which the business falls into bankruptcy and legal steps are taking place to ensure creditors or liquidation occurs. This is to ensure that the investment plan can make a profit for investors rather than making a loss. The value of the investment affected the confidence level of the investors by putting in their funds in the stock market. Prediction makes formerly is to prevent a business from sudden fall into bankruptcy. Altman Z-score and Logit model are implemented to predict the chance of bankruptcy. 40 companies were taken for prediction, 20 out of 40 companies are financial distress companies and the other 20 companies are non-financial distress companies. This paper is to help investors to have a good analysis for their investment decision. Logit model shows that the result from the calculation probability which is more than 0.5 as financial distress, less than 0.5 consider as non-financial distress, and showed that the result is predicted 92% of the analyses. The results show that there is a significant 5% level are sales to total assets, shareholders’ fund to total liabilities, cash from operating to total liabilities in the logit model for prediction.
format	Thesis
qualification_name	other
qualification_level	Master's degree
author	Ong, Gek Hwa
author_facet	Ong, Gek Hwa
author_sort	Ong, Gek Hwa
title	Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
title_short	Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
title_full	Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
title_fullStr	Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
title_full_unstemmed	Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia
title_sort	evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in malaysia
granting_institution	Universiti Utara Malaysia
granting_department	School of Economics, Finance & Banking
publishDate	2021
url	https://etd.uum.edu.my/11142/1/s826698_01.pdf https://etd.uum.edu.my/11142/2/s826698_02.pdf
_version_	1804888199608139776

Evaluation of bankruptcy prediction models and the effectiveness on listed companies in the stock market in Malaysia

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