本研究旨在分析台灣上市公司外匯避險和資本結構策略的運用。本文利用資本市場法，作為外匯曝險衡量模型，並利用預期和非預期的匯率變動探討對企業價值的影響是否有顯著差異，本文以2007~2009年期間的月頻率資料，篩選摩根台灣指數基金(MSCI Taiwan Index Fund-March 09, 2010)成分股共108家台灣上市公司為樣本對象，並進一步利用所量化出的外匯曝險，應用至公司資本結構上，採平衡追蹤資料(balanced panel data)進行分析，探討外匯曝險與其他影響因子對公司資本結構的關係。
而研究結果發現，在外匯曝險衡量方面，在2007~2009年間，不論是預期或非預期外匯變動下，負值的外匯曝險係數家數明顯超越正值的外匯曝險係數家數，此研究結果也符合了台灣為一個出口導向的經濟體，當台幣相對貶值時，使得出口較具競爭力，企業的營收增加。此外，從顯著的企業樣本來看，金融證券業占大多數，顯示出匯率變動對金融證券業的影響尤其嚴重。
在資本結構上，本研究以營運風險、公司成立年數、抵押資產價值、自由現金流量、外匯風險、成長率、稅盾效果、獲利性和公司規模共九個因子作為影響資本結構的變數，在Panel data固定效果模型中，除了成長性和公司規模兩變數在1%顯著水準之下呈現正相關，其餘變數為顯著負相關。且該模型對公司資本結構的解釋能力相當高，Panel data固定效果模型調整後的R2為78.96%。
最後，本研究將產業別列入考量變數之一，結果發現，電子業與非電子業在資本結構決定因素上有顯著差異，且顯示電子業公司的負債比率較低，符合現實情況下，電子業公司在有資金需求時，大多不選擇舉債而較常採取權益融資的方式。而電子業受到外匯曝險對資本結構的影響力並不顯著，表示外匯曝險對公司負債比率並不會因為產業別而有不同的影響力。 / This study examines the foreign exchange rate exposure and capital structure strategy for the Taiwan’s Corporations. The research sample is MSCI Taiwan Index Fund, and the sample period is 2007 to 2009. To see how foreign exchange rate exposure affects the value of corporations, this study uses Capital Market Approach to be the model. Moreover, this study uses balanced panel data to see how exchange rate exposure and other variables affect the strategy of capital structure.
According to the result, the numbers of negative significant samples are greater than the numbers of positive significant samples no matter when measured in expected exchange rate exposure or in unexpected exchange rate exposure. This result can exactly explain that Taiwan is an export-dominated economy. When Taiwan dollar depreciates, which means corporations in Taiwan could improve export competitiveness, thus increasing profits. Moreover, this study found that exchange rate exposure has a greater impact especially on the finance and security industry.
In the capital structure part, this study selects nine variables to see how they affect the capital structure, including business risk, age, collateral value of assets, free cash flows, foreign exchange risks , growth, non-debt tax shields, profitability and size. In panel data fixed effect model, growth and size are found to be positive significant in 99% confidence level; other variables are found to be negative significant. Furthermore, the coefficient of determination, R2 of this panel data fix effect regression model is 78.96%, which means the regression line has a high explanatory power to explain the capital structure.
| Identifer | oai:union.ndltd.org:CHENGCHI/G0097357029 |
| Creators | 蔡雅婷 |
| Publisher | 國立政治大學 |
| Source Sets | National Chengchi University Libraries |
| Language | 中文 |
| Detected Language | English |
| Type | text |
| Rights | Copyright © nccu library on behalf of the copyright holders |
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