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研究生:高韻雯
研究生(外文):GAO, YUN-WEN
論文名稱:國際費雪效果之再檢定與套利行為 -分量對分量迴歸之應用
論文名稱(外文):Re-testing of international Fisher effect and arbitrage behavior: An application of quantile-on-quantile regression
指導教授:吳博欽吳博欽引用關係劉曉燕劉曉燕引用關係
指導教授(外文):WU, PO-CHINLIU, SHIAO-YEN
口試委員:吳博欽劉曉燕黃財源蕭瑞銘
口試委員(外文):WU, PO-CHINLIU, SHIAO-YENHUANG, TSAI-YUANHSIAO, JUEI-MING
口試日期:2023-07-11
學位類別:碩士
校院名稱:中原大學
系所名稱:國際經營與貿易學系
學門:商業及管理學門
學類:貿易學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:中文
論文頁數:48
中文關鍵詞:國際Fisher效果分量單根檢定分量迴歸模型分量對分量迴歸模型利率差距
外文關鍵詞:International Fisher effectquantile unit root testquantile regression modelquantile-on-quantile regression modelinterest rate differential
DOI:10.6840/cycu202301709
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本研究以2007年8月至2022年4月期間台灣主要六大出口貿易國 (中國、美國、日本、韓國、馬來西亞、越南) 為對象,分別採用分量迴歸 (quantile regression, QR) 與分量對分量迴歸 (quantile-on-quantile regression, QQR) 方法評估國際Fisher效果 (IFE) 的適用性,並探討套利行為。實證結果摘錄如下:
(一)在QR模型下,以長期利率差距 (LRR) 或短期利率差距 (SRR) 進行估計時,IFE在台灣與其六個主要出口貿易國的結論是分歧的,且絕大多數是違反IFE。LRR估計係數顯示,新台幣相對於人民幣 (在所有五個分位數) 與美元 (θ =0.90) 過度升值,相對於日圓 (θ =0.25、0.50與0.75) 升值不足;新台幣相對於令吉 (θ =0.10) 與越南盾 (θ =0.25) 則應升值卻是貶值的。此外,SRR估計係數顯示,在絕大多數的情況下,新台幣兌人民幣與日圓有過度升值情形;新台幣兌令吉並未升值卻是貶值;在θ =0.10時,新台幣兌越南盾有過度升值情形,而在θ =0.90時,新台幣兌越南盾不升值卻是貶值。
(二)在QQR模型下,IFE的估計結果隨採用LRR或SRR,以及各種 ( , θ) 組合的不同而存在不對稱或非線性的結果。此外,無論採用LRR或SRR估計IFE,各種 ( , θ) 組合下,利率差距的估計係數均顯著異於1,顯示違反IFE。在LRR的最大估計係數中,集中在極端的 ( , θ) 組合上,例如:中國、韓國、馬來西亞與美國的 (0.05, 0.95)。在LRR的最小估計係數中,主要亦集中在極端的 ( , θ) 組合上,例如:韓國、馬來西亞與美國的 ( , 0.05)。在SRR的最大估計係數中,集中在極端的 ( , θ) 組合上,例如:中國、馬來西亞與美國的 (0.9或0.95, 0.05)。在SRR的最小估計係數中,主要亦集中在極端的 ( , θ) 組合上,例如:中國、日本、韓國、馬來西亞與美國的 (0.05或0.10, 0.05)。
(三)根據QQR模型的最大與最小估計係數可以進行套利行為,例如,以LRR的最大估計係數進行套利,則對中國、韓國、馬來西亞與美國而言,當 ( , θ)=(0.05, 0.95) 時,資金移往這些國家存在套利空間。以LRR的最小估計係數進行套利,則對韓國、馬來西亞與美國而言,當 ( , θ)=( , 0.05) 時,資金移往台灣存在套利空間。以SRR的最大估計係數進行套利,則對於中國、馬來西亞與美國而言,當 ( , θ)=(0.9或0.95, 0.05) 時,資金移往台灣存在套利空間。以SRR的最小估計係數進行套利,則對中國、日本、韓國、馬來西亞與美國而言,當 ( , θ)=(0.05或0.1, 0.05) 時,資金移往台灣存在套利空間。

This thesis takes Taiwan’s six major export countries (China, USA, Japan, South Korea, Malaysia, and Vietnam) as objects from August 2007 to April 2022 and uses quantile regression (QR) and quantile-on-quantile regression (QQR) approaches to assess the applicability of the International Fisher Effect (IFE) and explore arbitrage behavior. The empirical results are summarized as follows:
First, under the QR model, when estimated by long-term interest rate gap (LRR) or short-term interest rate gap (SRR), the conclusions of IFE between Taiwan and its six major export countries are divergent, and most of them violate IFE. The estimated coefficients of LRR show that the NT dollar has over-appreciated against the renminbi (at all five quantiles) and the US dollar (θ =0.90), under-appreciated against the Japanese yen (θ =0.25, 0.50, and 0.75), and over-appreciated against the Vietnam Dong (θ =0.25). The estimated coefficients of SRR show that in most cases, the NT dollar appreciates excessively against the RMB and the Japanese yen and depreciates instead of appreciating against the Ringgit. In addition, when θ =0.10, the NT dollar appreciates excessively against the Vietnamese Dong, and when θ =0.90, the NT dollar depreciates against the Vietnam Dong instead of appreciating.
Second, under the QQR model, the estimation results of IFE show asymmetric or nonlinear results depending on the use of LRR (or SRR) and various ( , θ) combinations. Regardless of using LRR or SRR to estimate IFE, under various ( , θ) combinations, the estimated coefficients of the interest rate differential are significantly different from one, indicating a violation of IFE. The largest estimated coefficients of LRR focus on the extreme combinations of ( , θ), such as (0.05, 0.95) for China, Korea, Malaysia, and the USA, and the smallest estimated coefficients of LRR also mainly concentrate on the extreme combinations of ( , θ), for example, ( , 0.05) in South Korea, Malaysia, and the USA. The largest estimated coefficients of SRR focus on the extreme combinations of ( , θ), for example, (0.9 or 0.95, 0.05) for China, Malaysia, and the USA, and the smallest estimated coefficients of SRR also mainly concentrate on the extreme combinations of ( , θ), such as (0.05 or 0.10, 0.05) for China, Japan, Korea, Malaysia, and the USA.
Third, according to the largest and smallest estimated coefficients of the QQR models, arbitrage can be carried out. For example, when ( , θ) =(0.05, 0.95), the estimated coefficient of LRR is largest for China, South Korea, Malaysia, and the USA, and funds can move into these countries to get arbitrage profit. When ( , θ) =( , 0.05), the estimated coefficient of LRR is smallest for South Korea, Malaysia, and the USA, and funds can move into Taiwan to get arbitrage profit. When ( , θ) =(0.9 or 0.95, 0.05), the estimated coefficient of SRR is largest for China, Malaysia, and the USA, and funds can move into Taiwan to get arbitrage profit. When ( , θ) =(0.05 or 0.1, 0.05), the estimated coefficient of SRR is smallest for China, Japan, South Korea, Malaysia, and the USA, and funds can move into Taiwan to get arbitrage profit.

目錄

摘要 Ⅰ
Abstract Ⅱ
致謝 Ⅳ
目錄 V
圖目錄 VI
表目錄 Ⅶ
第壹章 前言 1
第一節 緒論 1
第二節 研究目的 3
第三節 研究流程與架構 4
第貳章 文獻回顧 6
第一節 國際費雪效果 6
第二節 分量對分量迴歸方法 9
第參章 實證模型 11
第一節 國際Fisher效果 11
第二節 分量迴歸模型 13
第三節 分量對分量迴歸模型 14
第肆章 檢定方法 16
第一節 ADF單根檢定 16
第二節 分量單根檢定 17
第伍章 實證結果 18
第一節 資料來源及其特性 18
第二節 分量迴歸估計結果 23
第三節 分量對分量迴歸估計結果 26
第陸章 結論與建議 36
第一節 結論 36
第二節 政策建議 38
參考文獻 39 
圖目錄
圖1-1 研究流程 5
圖5-1分量對分量迴歸估計結果圖示 33


表目錄
表5-1 變數說明 18
表5-2 敘述統計結果 20
表5-3 分量單根檢定結果 21
表5-4 分量迴歸(QR)估計結果-長期利率差距為解釋變數 24
表5-5 分量迴歸(QR)估計結果-短期利率差距為解釋變數 25
表5-6 分量對分量迴歸估計係數最大值與最小值彙整 27
表5-7 分量對分量迴歸估計結果與套利資金移動方向 35
附表5-1 各變數主要分位數對應數值 41

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