自2008年全球金融風暴後，臺灣與美國的匯率與股票市場間逐漸形成不對稱的關係，在此情況下，匯率與股票的投資散戶要掌握適當的買賣股票及匯率時間點以獲取利潤，十分不容易。因此，本研究之主要目的是透過一般投資人可獲取的股價指數及匯率資料，結合關聯結構(Copula) 模型之不對稱相關性(asymmetric dependence property) 與指數加權移動平均(Exponential Weight Moving Average Control Chart, EWMA) 管制圖, 發展出一套決定股票與匯率最佳買賣時間點的方法，以供買賣股票與匯率的投資人參考。本研究藉由2005年至2012年的臺灣與美國匯率與股票市場資料，應用Copula 模型探討這些資料之不對稱相關性，再依據此模擬臺灣與美國匯率價格與股票指數間的關聯結構，建構EWMA 管制圖來觀察臺灣股票指數與美國股票指數的走勢，並找出買賣股票與匯率的最佳時間點。本研究最後利用S&P500指數、臺灣50指數與新臺幣兌美元的匯率資料來說明本研究所建立之EWMA 管制圖及並據此找出股票與匯率之最佳買賣時間點確實有效。

Stating from financial crisis happened in 2008, the relationship between exchange rates has become asymmetric, and so is the relationship between stock markets in Taiwan and USA. Under this circumstance, it is difficult for individual investors to grasp the proper timing for trading stock and exchange rates to make a profit. Therefore, the main idea of this study is to combine the asymmetry dependence property of Copula model and Exponential Weight Moving Average (EWMA) Control Chart to develop a strategy for determining the best timing to trade stock and exchange rates. This study utilizes the data which can be easily obtained by the investors, so that the proposed method can be widely used by individual stock or exchange rates investors. The data of exchange rates and stock index of Taiwan and USA from 2005 to 2012 were investigated using Copula model to detecting the asymmetric dependence between the stock index and exchange rates for two countries. These results are then utilized to simulate the data of exchange rates and stock index of Taiwan and USA to construct an Exponential Weight Moving Average (EWMA) Control Chart. By monitoring the trend of EWMA control chart, the best timing for trading the stocks and US dollars can be determined. Finally, this study use the stock index of Taiwan 50, S&P500 and the exchange rates between Taiwan and USA to verify that the proposed method is efficient.