本研究主要利用Granger因果關係檢定及向量自我迴歸模型來探討新台幣與日幣、韓圜、在岸人民幣、離岸人民幣匯率兩兩變數間之關聯性，期能提供於外匯市場交易之人員在實務操作時作為判斷新台幣短期匯率走勢及擬定交易或避險策略之參考。研究期間為2011年1月3日至2016年6月30日之日資料，實證結果如下:
一、在共整合檢定中，發現新台幣與在岸人民幣存有共整合向量，顯示兩變數間具有長期均衡關係；日幣、韓圜、離岸人民幣與新台幣間則不具有長期均衡關係。進一步透過向量誤差修正模型分析當新台幣與在岸人民幣偏離長期均衡的共整合關係式時，發現兩者修正調整的幅度均不大。
二、從Granger因果關係檢定結果發現，新台幣匯率變動率和日幣、韓圜、在岸人民幣及離岸人民幣匯率變動率之間皆具有單向的因果關係，即新台幣匯率變動率均領先其他四種貨幣；而日幣和韓圜間則具有雙向回饋關係。
三、由衝擊反應分析可得知，所有研究變數均對自身衝擊反應最大，接下來便快速收斂為零。
四、預測誤差變異數分解結果顯示，新台幣、日幣、離岸人民幣其自身解釋程度都相當高，推論此三個變數均不易受外來因素影響。

The main purpose of this study is to analyze the co-movements of NTD and East Asian currencies, which including JPY, KRW, CNY, and CNH by applying Granger Causality Test and VAR Model. The sample period runs from January 3, 2011 to June 30, 2016, yielding 1,408 observations. The empirical results are as follows:
1. There is a cointegrating vector between NTD and CNY, which means there is a long-run equilibrium relationship between these two variables by using Johansen Cointegration Test. Furthermore, through the VECM model, it is found that there is no significant adjustment when NTD and CNY are out of the long-term equilibrium.
2. According to Granger Causality Test, the movement of NTD is Granger-causes the movements of JPY, KRW, CNY, and CNH. There is a feedback system between the movement of JPY and the movement of KRW.
3. The result of Impulse Response Analysis shows that all the research variables have the greatest impact on their own shocks in the short-term period, then quickly convergence to zero.
4. The result of Forecast Error Variance Decomposition shows that NTD, JPY and CNH can be mostly explained by itself than other variables, implying these three variables are not affected by exogenous factors easily.

一、中文部份
王明昌、丁裕家(2013)，台灣與東協國家匯率及總體經濟動態關聯性分析，健行
學報，Vol.33 No.4，頁59-78。
吳秉澤、林聖斌 (2015)，臺灣及兩岸三地之匯率聯動性--以Copula-GARCH模
型分析，臺灣銀行季刊，Vol.66 No.3，頁51-84。
李堯賢、王譯賢、李玫郁(2015)，大數據資料下新台幣匯率與日圓、韓元之連動
研究，臺灣銀行季刊，Vol.66 No.4，頁56-74。
周國偉、楊呫予(2012)，雙邊匯率、多方匯率、與總體經濟基本面：以我國為例，
東吳經濟商學學報，第七十六期，頁33-54。
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，Vol.
46 No.1，頁75-111。
陳家鋐(2010)，探討金融風暴前及風暴期間亞洲國家匯率對我國匯率的影響，國
立臺北大學國際財務金融碩士在職專班，碩士論文。
陳益明(2007)，影響新台幣匯率基本因素之分析，商學學報，第十五期，頁113-
129。
彭成瑋(2014)，長短期匯率預測研究-以台幣日圓為例，國立臺北大學經濟學系，
碩士論文。
彭德明(2013)，東亞主要新興經濟體匯率變動率波動與共變程度之實證分析，中
央銀行季刊，Vol.35 No.3，頁3-36。
黃國安(2014)，新台幣兌美元匯率預測模型之比較，國防大學管理學院財務管理
學系，碩士論文。
楊呫予(2012)，名目有效匯率與總體經濟基本面關聯性之研究:以我國為例，主
計季刊，Vol.53 No.2，頁45-63。
謝思柔(2014)，亞洲六種貨幣互動影響之探討，國立雲林科技大學財務金融系，
碩士論文。

二、英文部份
Lee, J. W., (2015), “Dynamic Relationships between Exchange Rates and Foreign Direct Investment: Empirical Evidence from Korea,”Asian Economic Journal, Vol. 29, No. 1, p73-90.
Riadh, E. A., (2016), “On the Comovements among European Exchange Rates and Stock Prices: A Multivariate Time-Varying Asymmetric Approach,”Journal of Applied Finance and Banking, Vol. 6, No. 1, p53-79.
Su, C.-W., (2012), “The relationship between exchange rate and macroeconomic variables in China,”Proceedings of Rijeka Faculty of Economics, Journal of Economics and Business, Vol. 30, No. 1, p33-56.
Vyas, I., Prasad, N. and Mishra, A. K., (2011), “Causal Nexus between Stock Price, Demand for Money, Interest Rate, Foreign Institutional Investment, and Exchange Rates in India: A Post Subprime Crisis Analysis,”Indonesian Capital Market Review, Vol. 3, No. 2, p81-100.
Yang, S.-Y. and Doong, S.-C., (2004), “Price and Volatility Spillovers between Stock Prices and Exchange Rates: Empirical Evidence from the G-7 Countries,” International Journal of Business and Economics, Vol. 3, No. 2, p139-153.