本文探討結構式模型是否具有解釋名目匯率變動之能力，並觀察組合模型能否改善單一模型之預測能力。我們使用以下四種匯率預測模型：未拋補利率平價模型(UIP)、購買力平價模型(PPP)、貨幣學派模型(MF)和非對稱性之泰勒法則(TR)，利用遞迴樣本迴歸估計法(Recursive Regression)，對英國、日本、加拿大、瑞士及美國的名目匯率進行樣本外預測，將不具飄移項之隨機漫步模型作為比較基準，以Theil’s U比例、CW檢定和DM檢定為準則，藉以衡量四種結構式模型之匯率預測能力。實證結果顯示，在單一模型預測結果中，Theil’s U比例下的美國在UIP模型中的短期預測能力優於隨機漫步，其餘四國的預測能力和隨機漫步模型並無顯著差異，在CW檢定下，四種結構式模型以PPP模型的表現最為出色。而在組合模型預測結果中，美國之實證結果可觀察出在Theil’s U比例及CW檢定中，組合模型在短期下具有改善匯率預測之能力，日本與瑞士在CW檢定中，組合模型在長期下也有擁有改善匯率預測之能力，其餘國家之組合模型大致上皆未能擊敗隨機漫步模型。

This paper not only examines whether structural models have the capability to explain the fluctuation of nominal exchange rates, but also observes whether a combined model could improve the predictability of a single model. We use the following four exchange rate prediction models: the uncovered interest parity model (UIP), the purchasing power parity model (PPP), the flexible price monetary model and the asymmetric Taylor rule model to predict the nominal exchange rates of United Kingdom, Japan, Canada, Switzerland and United State. We adopted a recursive regression to conduct out-of-sample forecasts and used the Theil’s U ratio, the CW test and the DM test to evaluate the predictability of structural models. We found that the performance of the UIP model in United State with Theil’s U ratio is better than the driftless random walk in the short run. But there is no difference between RW and structural models in other four countries. PPP model outperforms other structural models in the CW test. On the other hand, we found that combined models have the capability to improve the predictability of single models in United State in the short run.
We also found that combined models of Japan and Switzerland have improved the predictability of single models with CW test in the long run. In general, most of combined models couldn’t outperform driftless random walk.

論文審定書 i
謝辭 ii
摘要 iii
Abstract iv
表次 vi
第一章 緒論　1
　第一節　研究目的與動機　1
　第二節　研究流程　2
第二章　文獻回顧　3
第三章　理論模型與研究方法　14
　第一節　模型建立　14
　第二節　預測方法　19
　第三節　績效評估與檢定　20
第四章　實證結果　24
　第一節　資料來源　24
　第二節　單一模型預測結果　26
　第三節　組合模型預測結果　30
　第四節　Robustness　38
第五章　結論　46
參考文獻　49
　中文部分　49
　英文部分　49

中文部分

1. 李建強、張倉耀、李起銓、林欣怡(2010)，“匯率與總體基本面之非線性動態關係－G-7國家的實證研究”，經濟與管理論叢，第6卷第2期，頁203-228。
2. 周國偉、曾翊恆(2008)，“總體經濟基本面的預測表現－台灣與其他六國匯率模型之實證分析”，台灣經濟論衡，第6卷第8期，頁36-65。
3. 郭炳伸、藍青玉(2015)，“模型組合與新台幣匯率預測”，臺灣經濟預測與政策，第46卷第1期，頁75-111。
4. 陳旭昇(2013)，“時間序列分析：總體經濟與財務金融之應用”，臺北：東華書局，第二版修訂。
5. 楊奕農(2009)，“時間序列分析：經濟與財務上應用”，臺北：雙葉書廊，第二版。
6. 賴景昌(2007)，“國際金融理論：基礎篇”，臺北：華泰文化，第二版。
7. 賴景昌(2011)，“總體經濟學”，臺北：雙葉書廊，第三版。

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