:::

詳目顯示

回上一頁
題名:日本首相安倍的寬鬆貨幣政策下--臺幣、日圓、韓元之關聯結構分析
書刊名:商略學報
作者:李沃牆 引用關係林惠娜 引用關係朱珈瑩
作者(外文):Lee, Wo-chiangLin, Hui-naChu, Chia-ying
出版日期:2016
卷期:8:2
頁次:頁119-134
主題關鍵詞:寬鬆貨幣安倍經濟學競貶效果Copula關聯結構Quantitative easingAbenomicsDepreciation effectCopula
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:3
  • 點閱點閱:8
本研究的目的在透過ARMAX-GJR-GARCH-Copula Type模型檢驗台幣、日圓、韓元之間在實施寬鬆貨幣政策前後是否存在競貶效果。實證結果顯示,無論是全樣本或安倍實施寬鬆貨幣政策前後,日圓對台幣及韓元匯率均數方程式影響皆呈現顯著正向影響。變異數方程式參數估計而言,全樣本、寬鬆貨幣政策前呈顯著影響,意涵安倍實施寬鬆貨幣政策對市場有顯著衝擊。除了安倍實施寬鬆貨幣政策前,韓元匯率的不對稱性不顯著外,其餘皆具顯著性。透過五種不同的Copula函數分別配適全樣本、安倍實施寬鬆政策前、後,日圓與台幣、日圓與韓元及台幣與韓元三組的匯率關聯結構,求出列相關係數(Kendall's tau)。結果發現,日圓與台幣、日圓與韓元的相關程度無論在全樣本、安倍實施寬鬆政策前、後均很小;意涵台灣及韓國央行均能力守匯率的穩定性,不受日圓貶值而競貶。但安倍實施寬鬆政策後,其相關性稍微提高。顯示台灣與韓國之出口貿易競爭關係激烈,而匯率是影響出口的重要關鍵。
The study uses the asymmetric ARMAX-GJR-GARCH-Copula Type model to examine whether NTD, YEN, and KRW have the depreciation effect before and after implementation of the quantitative easing policy in Japan. The empirical results show that no matter full example, before, or after the policy, the YEN had showed a positive significant effect on NTD and KRW in the mean equation. As variance equation, full sample and before the policy period also found a significant effect of quantitative easing policy, meaning the shock of the policy had great effect on the markets. No significant asymmetry effect in KRW exchange rate, the others remain significant. This study further fit five copula functions on the JPY vs TWD, JPY vs KRW and NT vs KRW exchange rate to the whole sample, before and after the policy. According the correlation coefficient (Kendall's tau), the results showed that the relations of JPY vs TWD and JPY vs KRW's are small in terms of the full sample and before the policy, which means that Taiwan and Korea’s central banks have the ability to keep the exchange rate stability, when competing against the JPY. However, the result shows slightly increase its relevance after the policy. The degree of relation between NT and KRW both in the full sample, and before the policy are high, showing export trade competition between Taiwan and South Korea's is fierce. The exchange rate is the key to influence exports.
期刊論文
1.Schweizer, B.、Wolff, E. F.(1981)。On Nonparametric Measures of Dependence for Random Variables。Annals of Statistics,9(4),879-885。  new window
2.Junker, M.、Szimayer, A.、Wagner, N.(2006)。Nonlinear Term Structure Dependence: Copula Functions, Empirics, and Risk Implications。Journal of Banking and Finance,30(4),1171-1199。  new window
3.李沃牆(20130900)。日本量化寬鬆當道,另一個失落或崛起的十年?。會計研究月刊,334,76-82。  延伸查詢new window
4.Manner, H.、Reznikova, O.(2012)。A Survey on Time-Varying Copulas: Specification, Simulations, and Application。Econometric Review,31(6),654-687。  new window
5.Rodriguez, J. C.(2007)。Measure Financial Contagion a Copula Approach。Journal of Empirical Finance,14(3),401-423。  new window
6.Chiou, S. C.、Tsay, R. S.(2008)。A Copula-based Approach to Option Pricing and Risk Assessment。Journal of Data Science,6,273-301。  new window
7.Hsu, C. C.、Tseng, C. P.、Wang, Y. H.(2008)。Dynamic Hedging with Futures: a Copula- based GARCH Model。Journal of Futures Markets,28(11),1095-1116。  new window
8.Palaro, H. P.、Hotta, L. K.(2006)。Using Conditional Copula to Estimate Value at Risk。Journal of Data Science,4,93-115。  new window
9.Sklar, A.(1959)。Fonctions de Repartition a n Dimensions et leurs Marges。Publications e l’Institut de Statistique de l’Universite de Paris,8,229-231。  new window
10.Huang, J. J.、Lee, K. J.、Kuo, L.、Liang, H.、Lin, W. F.(2009)。Estimating Value at Risk of Portfolio by Conditional Copula-GARCH Method。Insurance Mathematics and Economics,45(3),315-324。  new window
11.Schwarz, Gideon(1978)。Estimating the Dimension of a model。The Annals of Statistics,6(2),461-464。  new window
12.賴奕豪、江福松、林煌傑(20100700)。極端報酬下亞洲股市之蔓延效果:應用Copula分析法。經濟與管理論叢,6(2),247-270。new window  延伸查詢new window
13.Glosten, Lawrence R.、Jagannathan, Ravi、Runkle, David E.(1993)。On the Relation Between the Expected Value and the Volatility on the Nominal Excess Returns on Stocks。Journal of Finance,48(5),1779-1801。  new window
14.Lee, W. C.、Lin, H. N.(2010)。The Dynamic Relationship between Gold and Silver Futures Markets based on Copula-AR-GJR-GARCH Model。Middle Eastern of Finance and Economics,7,118-129。  new window
學位論文
1.沈青孺(2013)。美國總體經濟變數與通貨膨脹關聯性結構探討-Copula模型之應用(碩士論文)。淡江大學。  延伸查詢new window
2.林勝宏(2004)。國際股市關聯性結構之研究--Copula模型之應用(碩士論文)。國立臺灣科技大學。  延伸查詢new window
3.黃坤銘(2010)。次級房貸危機及金融海嘯下美國股市與公債期現貨市場動態連動性之研究--VEC DCC GJR-GARCH 模型與VEC Copula GJR-GARCH-skewed-t 模型之應用(碩士論文)。國立臺北大學。  延伸查詢new window
圖書
1.楊奕農(2005)。時間序列分析--經濟與財務上之應用。臺北:雙葉書廊有限公司。  延伸查詢new window
圖書論文
1.Akaike, H.(1973)。Information Theory and an Extension of the Maximum Likelihood Principle。Second International Simposium on Information Theory。  new window
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關博士論文
 
無相關書籍
 
無相關著作
 
QR Code
QRCODE