The factors affect leverage of listed construction companies (top 20 in Malaysia) / Mohd Naquiddin Tajuddin

The financial management and operation management of construction companies are very important. Failure to fulfill these will result in bad company's performance. This usually happens because of bad financial management and lack of capital. Construction companies tend to use their own money fir...

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Bibliographic Details
Main Author: Tajuddin, Mohd Naquiddin
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/95796/1/95796.pdf
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Summary:The financial management and operation management of construction companies are very important. Failure to fulfill these will result in bad company's performance. This usually happens because of bad financial management and lack of capital. Construction companies tend to use their own money first in settling the development before getting the profit (Baharuddin, N. S., Khamis, Z., Wan Mahmood, W. M. , & Dollah, H. , 2011). Capital structure theories claim that the mix of debt and equity are very important. Therefore, there is a need to investigate this study. This research is conducted to study the factors that affect the leverage of firms. It focuses on the firms from construction sector in Malaysia. The firms are also listed in Bursa Malaysia. The internal determinants that can give effects towards the leverage will be analysed carefully. Leverage is considered as the dependent variable in this study and it will be measured by debt ratio. Debt ratio that is expressed by total debt divides total asset is the proxy that will be used in this study. Four independent variables are chosen in this study, which are firm size, company growth, asset tangibility and profitability. 20 listed construction companies in Malaysia are involved in this research and the data collected is based on financial report of the companies. Panel data will be used in this study and all the data is secondary data. This study is also based on 5 years data from year 2012-2016. Total of 100 observations will be gained. Last but not least, this study uses the Panel Ordinary Least Square (POLS) method to estimate the relationship and significance of the variables.