Estimation and Prediction of Financial Distress: Non-Financial Firms in Bursa Malaysia

被引:4
|
作者
Hiong, Hii King [1 ]
Jalil, Muhammad Farhan [1 ]
Seng, Andrew Tiong Hock [2 ]
机构
[1] Univ Coll Technol Sarawak, Sch Business & Management, 1 Jalan Univ, Sarawak 96000, Malaysia
[2] NIIT Coll, Sarawak, Malaysia
来源
关键词
Financial Distress; Altman's Z-Score Model; Non-Financial Companies; Financial Ratios; Malaysia Stock Exchange; DISCRIMINANT-ANALYSIS; BANKRUPTCY RISK; RATIOS; PROFITABILITY; DISCLOSURE; CREDIT; CYCLE;
D O I
10.13106/jafeb.2021.vol8.no8.0001
中图分类号
F [经济];
学科分类号
02 ;
摘要
Altman's Z-score is used to measure a company's financial health and to predict the probability that a company will collapse within 2 years. It is proven to be very accurate to forecast bankruptcy in a wide variety of contexts and markets. The goal of this study is to use Altman's Z-score model to forecast insolvency in non-financial publicly traded enterprises. Non-financial firms are a significant industry in Malaysia, and current trends of consolidation and long-term government subsidies make assessing the financial health of such businesses critical not just for the owners, but also for other stakeholders. The sample of this study includes 84 listed companies in the Kuala Lumpur Stock Exchange. Of the 84 companies, 52 are considered high risk, and 32 are considered low-risk companies. Secondary data for the analysis was gathered from chosen companies' financial reports. The findings of this study show that the Altman model may be used to forecast a company's financial collapse. It dispelled any reservations about the model's legitimacy and the utility of applying it to predict the likelihood of bankruptcy in a company. The findings of this study have significant consequences for investors, creditors, and corporate management. Portfolio managers may make better selections by not investing in companies that have proved to be in danger of failing if they understand the variables that contribute to corporate distress.
引用
收藏
页码:1 / 12
页数:12
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