题名

日本首相安倍的寬鬆貨幣政策下-台幣、日圓、韓元之關聯結構分析

并列篇名

The Copula Relationship of Taiwan, Japan and Korea’s Foreign Exchange Market under Quantitative Easing Policy of Japan

作者

李沃牆(Wo-Chiang Lee);林惠娜(Hui-Na Lin);朱珈瑩(Chia-Ying Chu)

关键词

寬鬆貨幣 ; 安倍經濟學 ; 競貶效果 ; Copula關聯結構 ; Quantitative Easing ; Abenomics ; Depreciation Effect ; Copula

期刊名称

商略學報

卷期/出版年月

8卷2期(2016 / 06 / 01)

页次

119 - 134

内容语文

繁體中文

中文摘要

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。

英文摘要

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.

主题分类 基礎與應用科學 > 資訊科學
社會科學 > 經濟學
社會科學 > 管理學
参考文献
  1. Akaike, H.(1973).Information Theory and an Extension of the Maximum Likelihood Principle.Second International Simposium on Information Theory
  2. Chiou, S. C.,Tsay, R. S.(2008).A Copula-based Approach to Option Pricing and Risk Assessment.Journal of Data Science,6,273-301.
  3. Glosten, L. R.,Jagannathan, R.,Runkle, D. E.(1993).On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks.Journal of Finance,48(5),1779-1799.
  4. Hsu, C. C.,Tseng, C. P.,Wang, Y. H.(2008).Dynamic Hedging with Futures: Copula-based GARCH Model.Journal of Futures Markets,28(11),1095-1116.
  5. 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.
  6. 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.
  7. 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.
  8. Manner, H.,Reznikova, O.(2012).A Survey on Time-Varying Copulas: Specification.Simulations, and Application. Econometric Review,31(6),654-687.
  9. Palaro, H. P.,Hotta, L. K.(2006).Using Conditional Copula to Estimate Value at Risk.Journal of Data Science,4,93-115.
  10. Rodriguez, J. C.(2007).Measure Financial Contagion a Copula Approach.Journal of Empirical Finance,14(3),401-423.
  11. Schwarz, G. E.(1978).Estimating the Dimension of a Model.The Annals of Statistics,6(2),461-464.
  12. Schwettzer, B.,Wolff, E.(1981).On Nonparametric Measures of Dependence For Random Variables.The Annals of Statistics,9,879-885.
  13. Sklar, A.(1959).Fonctions de Répartition à n Dimensions et Leurs Marges.Publications de l'Institut de Statistique de L'Universite de Paris, 8.
  14. 李沃牆(2013)。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。
  15. 沈青孺(2013)。碩士論文(碩士論文)。淡江大學財務金融學系研究所。
  16. 林勝宏(2004)。碩士論文(碩士論文)。國立台灣科技大學資訊管理學系。
  17. 黃坤銘(2010)。碩士論文(碩士論文)。臺北大學國際企業研究所。
  18. 楊奕農(2005)。時間序列分析-經濟與財務上之應用。台北:雙葉書廊出版。
  19. 賴奕豪、江福松、林煌傑(2010)。極端報酬下亞洲股市之蔓延效果。經濟與管理論叢,6(1),247-270。