建設公司資本結構最適化之研究
碩士 === 國立臺灣大學 === 土木工程學研究所 === 88 === Determining the firm’s leverage is always one of the most important financial decisions for building firms. Debt provides the company with benefits of financial leverage, but it also increases the probability of bankruptcy. The optimal capital structure is to ma...
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ndltd-TW-088NTU000151322016-01-29T04:14:31Z http://ndltd.ncl.edu.tw/handle/24517741570056095448 建設公司資本結構最適化之研究 周業修 碩士 國立臺灣大學 土木工程學研究所 88 Determining the firm’s leverage is always one of the most important financial decisions for building firms. Debt provides the company with benefits of financial leverage, but it also increases the probability of bankruptcy. The optimal capital structure is to maximize the company’s value through the trade-off between debt’s advantages and disadvantages. This study adopts easy-quantified factors to consider the benefits and costs brought from debts. This study assumes that the benefit brought from debt is to reduce company’s tax expenses, but the cost of debt is to increase the probability of bankruptcy and the expected value of bankruptcy cost. Moreover, this study also takes company’s non-debt tax shields into consideration. Under these assumptions, the purposes of this study, based on the optimal-capital-structure-based inferential model are to employ the mathematical methods to find out the optimal solution and to explore the influence applied by properties of building firms on parameters used in former model. This study is separated to two parts. First, this empirical study adapted the building firms, listed on T.S.E. as sample and employed Pearson Correlation Analysis and Grey Relational Analysis to find out the correlation among the capital structure and this model’s parameters. The second part, based on the established model, this study determines the optimum capital structure of the example company. The result of this study can be building firms’ financial decision support and helps building firms to determine proportion of equity and debt. 曾惠斌 2000 學位論文 ; thesis 111 zh-TW |
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碩士 === 國立臺灣大學 === 土木工程學研究所 === 88 === Determining the firm’s leverage is always one of the most important financial decisions for building firms. Debt provides the company with benefits of financial leverage, but it also increases the probability of bankruptcy. The optimal capital structure is to maximize the company’s value through the trade-off between debt’s advantages and disadvantages. This study adopts easy-quantified factors to consider the benefits and costs brought from debts. This study assumes that the benefit brought from debt is to reduce company’s tax expenses, but the cost of debt is to increase the probability of bankruptcy and the expected value of bankruptcy cost. Moreover, this study also takes company’s non-debt tax shields into consideration. Under these assumptions, the purposes of this study, based on the optimal-capital-structure-based inferential model are to employ the mathematical methods to find out the optimal solution and to explore the influence applied by properties of building firms on parameters used in former model.
This study is separated to two parts. First, this empirical study adapted the building firms, listed on T.S.E. as sample and employed Pearson Correlation Analysis and Grey Relational Analysis to find out the correlation among the capital structure and this model’s parameters. The second part, based on the established model, this study determines the optimum capital structure of the example company. The result of this study can be building firms’ financial decision support and helps building firms to determine proportion of equity and debt.
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曾惠斌 |
author_facet |
曾惠斌 周業修 |
author |
周業修 |
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周業修 建設公司資本結構最適化之研究 |
author_sort |
周業修 |
title |
建設公司資本結構最適化之研究 |
title_short |
建設公司資本結構最適化之研究 |
title_full |
建設公司資本結構最適化之研究 |
title_fullStr |
建設公司資本結構最適化之研究 |
title_full_unstemmed |
建設公司資本結構最適化之研究 |
title_sort |
建設公司資本結構最適化之研究 |
publishDate |
2000 |
url |
http://ndltd.ncl.edu.tw/handle/24517741570056095448 |
work_keys_str_mv |
AT zhōuyèxiū jiànshègōngsīzīběnjiégòuzuìshìhuàzhīyánjiū |
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1718166898923798528 |