臺灣博碩士論文加值系統

外匯市場是世界上最具規模也是流動性最大的金融市場之一，且在資訊爆炸的時代下，各種訊息皆能迅速的被傳遞，因此，外匯市場的匯率變化日益劇烈，投資人不再只是考慮投資報酬率的高低，還有其風險控管的大小，尤其近期金融風暴之影響，使得全球各地金融市場產生巨幅波動，隨著金融市場的劇烈變化，外匯匯率之波動可能更形劇烈，因此，有必要就次貸風暴前後之外匯風險值(Value at Risk, VaR)作一比較，以提供外匯部位之持有者作一個參考。
本研究目的主要探討外匯市場風險值對於次貸風暴前後的問題，運用不同風險值模型(歷史模擬法、蒙地卡羅模擬法、變異數-共變異數模擬法，及ARMA-GARCH模擬法)來計算英鎊、歐元、日元、新台幣與美元在移動窗口30天、60天、125天與250天及99%與95%信賴水準下之風險值比較。
經實證研究發現:
1.各幣別在ARMA-GARCH 95%信賴水準下，穿透率較接近研究所設定的顯著水準，各期間的移動窗口表現較一致。
2.在LRcc檢定與Z檢定的準確檢定中，各幣別以95%信賴水準下所計的變異數-共變異數法與ARMA-GARCH法中的準確性結果較佳。
3.從RMSE效率性檢定來中可以得知，所有模型中，蒙地卡羅法所估計出的RMSE值最小效率性最佳，由99%信賴水準所估計出的RMSE值較小，較具有效率性，在各幣別中則是以台幣所估計出的RMSE結果較佳。
4.由於次貸風暴的發生，金融資產之市場價格波動加劇，各幣別在次貸後所需計提之風險值皆較次貸前為多，其中以英鎊的VaR波動幅度與VaR提列幅度最大。

The foreign exchange market is the most mobile and also the largest in the financial markets. At the current information boom, messages can be quickly passed on. Therefore, the foreign exchange rate changes rapidly day by day. The investors not only consider the return level of investments but also its risk management. Especially during the current financial crisis, created massive fluctuations in the global financial market. With the fluctuations, the current exchange rate would have a even more volatile fluctuation. Consequently, it is necessary to analyze the Value at Risk (VaR) of the foreign currency rate before and after the Sub-Prime crises.
This study focuses on the VaR of the foreign exchange market before and after the Sub-Prime crises, using different VaR models (such as historical simulation approach, Monte Carlo simulation approach, variance-covariance simulation approach, ARMA-GARCH simulation approach) to calculate USD against GBP, EUR, JPY and NTD on moving window of 30 days, 60 days, 125 days and 250 days with 99% or 95% confidence level of VaR.
The results are as follows:
1.With the currency set at ARMA-GARCH 95% confidence level, the penetration rate is closer than the set significant level and presented the same performance during each moving window.
2.In the LRcc test and Z test accuracy tests, in which each currency set at a 95% confidence level, the estimated variety value result shows a better outcome in both variance-covariance approach and ARMA-GARCH approach.
3.We can learn from the RMSE test, in all models, the RMSE value is best determined by the Monte Carlo approach, which estimation presents the smallest efficiency, on the other hand, the estimate for RMSE of 99% significant level is of smaller value, and also has more efficiency, amongst different currencies, NTD shows a better result of RMSE estimate.
4.As a result of the Sub-Prime crisis, the fluctuation in the financial market has become more volatile, all currencies have more VaR to consider than before the crisis, amongst them, GBP has the biggest VaR fluctuation rate and range.

中文摘要........................................................................................................................I
ABSTRACT..................................................................................................................III
誌謝...............................................................................................................................V
表目錄.......................................................................................................................VIII
圖目錄.........................................................................................................................IX
　
第一章　緒論...............................................................................................................1
　第一節　研究背景與機...........................................................................................1
　第二節　研究目的...................................................................................................3
　第三節　研究架構與流程.......................................................................................4
第二章文獻回顧...........................................................................................................6
　第一節　風險值的定義與起源...............................................................................6
　第二節　風險值的估計模型介紹...........................................................................7
　第三節　風險模型之驗證.....................................................................................10
　第四節　國內外風險值相關文獻探討.................................................................10
第三章　研究方法.....................................................................................................14
　第一節　各風險模型的介紹.................................................................................14
　第二節　風險值驗證.............................................................................................20
第四章　實證分析與結果.........................................................................................26
　第一節　資料來源與說明.....................................................................................26
　第二節　穿透率實證結果分析.............................................................................34
　第三節　條件涵蓋檢定與 檢定之準確性結果分析............................................39
　第四節　效率性檢定之結果分析.........................................................................44
　第五節　次貸後各幣別之VAR波動與VAR提列比例.........................................49
第五章　結論與建議 ................................................................................................51
　第一節　結論.........................................................................................................51
　第二節　研究建議與限制.....................................................................................53
參考文獻.....................................................................................................................54
　一、中文文獻.........................................................................................................54
　二、英文文獻.........................................................................................................54

　
附錄A美元兌各幣別之穿透次數統計......................................................................57
附錄B美元兌各幣別之VAR標準差與VAR平均值..................................................59
附錄C美元兌各幣別之LRcc與LRind檢定................................................................63
附錄D美元兌各幣別之報酬率與風險值走勢圖......................................................67

　
表目錄
　表4-1　 美元兌各幣別之匯率報酬率敘述性統計..............................................33
　表4-2　 英鎊99%信賴水準下之LRcc檢定與Z檢定............................................40
　表4-3　 歐元99%信賴水準下之LRcc檢定與Z檢定............................................40
　表4-4　 日圓99%信賴水準下之LRcc檢定與Z檢定............................................41
　表4-5　 新台幣99%信賴水準下之LRcc檢定與Z檢定........................................41
　表4-6　 英鎊95%信賴水準下之LRcc檢定與Z檢定............................................42
　表4-7　 歐元95%信賴水準下之LRcc檢定與Z檢定............................................43
　表4-8　 日圓95%信賴水準下之LRcc檢定與Z檢定............................................43
　表4-9　 新台幣95%信賴水準下之LRcc檢定與Z檢定........................................44
　表4-10　ARMA-GARCH 95%信賴水準下次貸前後VaR變動比例....................49

　
圖目錄
　圖1-1　 研究流程....................................................................................................5
　圖2-1　 信賴水準1-α下的VaR................................................................................6
　圖3-1　 計算歷史資料每期變動量......................................................................14
　圖4-1　 資料期間設計..........................................................................................26
　圖4-2　 研究步驟..................................................................................................27
　圖4-3　 計算移動窗口250天下的VaR.................................................................29
　圖4-4　 各幣別匯率報酬率之波動度..................................................................30
　圖4-5　 美元兌英鎊匯率走勢圖與匯率報酬率圖..............................................31
　圖4-6　 美元兌歐元匯率走勢圖與匯率報酬率圖..............................................32
　圖4-7　 美元兌日圓匯率走勢圖與匯率報酬率圖..............................................32
　圖4-8　 美元兌新台幣匯率走勢圖與匯率報酬率圖..........................................32
　圖4-9　 英鎊99%信賴水準下之穿透率...............................................................37
　圖4-10　歐元99%信賴水準下之穿透率..............................................................37
　圖4-11　日圓99%信賴水準下之穿透率..............................................................37
　圖4-12　新台幣99%信賴水準下之穿透率..........................................................37
　圖4-13　英鎊95%信賴水準下之穿透率..............................................................38
　圖4-14　歐元95%信賴水準下之穿透率..............................................................38
　圖4-15　日圓95%信賴水準下之穿透率..............................................................38
　圖4-16　新台幣95%信賴水準下之穿透率..........................................................38
　圖4-17　英鎊99%信賴水準下之RMSE檢定........................................................47
　圖4-18　歐元99%信賴水準下之RMSE檢定........................................................47
　圖4-19　日圓99%信賴水準下之RMSE檢定........................................................47
　圖4-20　新台幣99%信賴水準下之RMSE檢定....................................................47
　圖4-21　英鎊95%信賴水準下之RMSE檢定........................................................48
　圖4-22　歐元95%信賴水準下之RMSE檢定........................................................48
　圖4-23　日圓95%信賴水準下之RMSE檢定........................................................48
　圖4-24　新台幣95%信賴水準下之RMSE檢定....................................................48
　 圖4-25　次貸後VaR波動比例..............................................................................50
　 圖4-26　次貸後VaR提列比例..............................................................................50

一、中文文獻
1.辛喬利、孫兆東 (2009)。「次貸風暴：撼動世界經濟的金融危機，剖析次貸風暴的前因後果」。台北：梅霖文化事業有限公司。
2.林恩如 (2006)。「風險值衡量方法之匯率實證」。國立成功大學財務金融研究所碩士論文。
3.施欣華 (2007)。「匯率風險值之評估-不同風險值模型之應用」。國立高雄應用科技大學金融資訊研究所碩士論文。
4.財務金融研究中心 (1999)。「投資分析+MatLab應用」。台北：全華科技圖書公司。
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