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博碩士論文 etd-0625110-101357 詳細資訊
Title page for etd-0625110-101357
論文名稱
Title
工業國家匯率的非線性調整過程:追蹤資料LSTAR模型之實證分析
Nonlinear adjusted process of industry countries' exchange rate:empirical analysis of Panel STAR model
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
56
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2010-06-22
繳交日期
Date of Submission
2010-06-25
關鍵字
Keywords
匯率、平滑轉換自我回歸模型
STAR, exchange rate
統計
Statistics
本論文已被瀏覽 5823 次,被下載 20
The thesis/dissertation has been browsed 5823 times, has been downloaded 20 times.
中文摘要
摘要
本研究,針對比利時, 加拿大, 丹麥, 法國, 德國, 義大利, 日本, 西班牙, 英國, 美國這些國家,利用Van Dijk, D.; Terӓsvirta, T.; Franses, P.H.(2002)所提出的STAR延伸模型,來建立個別國家模型;利用Van Dijk, D.; Terӓsvirta, T.; González, A.(2005)所提出的追蹤資料STAR模型,來建立追蹤資料模型。接著進行診斷性檢定,最後分別和隨機遊走模型比較預測能力。
選取資料期間從1974年1月至2003年12月,共360筆月資料為樣本期間,並取2004年1月至2008年12月,共60筆月資料為樣本外期間,用其作樣本外預測。選取資料為1974年1月至2008年12月的匯率月資料和物價指數,以此探討名目匯率的技術性分析和名目匯率與實質匯率之間的可解釋性。
實證結果顯示,在個別國家模型中,所有國家都具有”11月”效應,並且日本的國家模型中,有統計上顯著水準的表示,日本政府存在干預外匯的政策;以及丹麥、法國、德國、義大利、西班牙、英國的國家模型中,有統計上顯著水準的表示,這些國家政府沒有參與干預外匯市場;其餘的國家,雖然沒有政府干預外匯的現象,但是統計上不顯著。在追蹤資料模型中,用實質匯率去解釋名目匯率,具有統計上顯著的非線性之調整現象,但是gamma質偏小,表示實質匯率和名目匯率之間,調整過程偏久,也就是說可能存在長期之下實質匯率可以解釋名目匯率,但是短期間則否。最後,用兩個模型進行預測,其預測結果,大部分皆比隨機遊走模型來為佳。
Abstract
Abstract
The purpose of this paper is to research the countries' exchange rates. The paper is organized around the empirical modeling method which is devised by Van Dijk, D.; Terӓsvirta, T.; Franses, P.H.(2002) and Van Dijk, D.; Terӓsvirta, T.; González, A.(2005). It consists of estimation, specification tests, and forecast stages.
The data is chosen from 1974M1 to 2008M12. We set the data from 1974M1 to 2003M12 as in-sample period, and from 2003M1 to 2008M12 as out-of-sample period. The macroeconomic variables considered in this paper include nominal exchange rates and real exchange rates.
We get four important empirical results in this paper. First, the STAR model shows that every countries exists “eleventh month effects”. Second, the coefficient of nonlinear in Denmark’s, France’s, Germany’s, Italy’s, Spain’s and UK’s model are statistically significant. This result implies that the government of Japan had been intervening significantly in foreign exchange markets. And the government of other countries had been not intervening in foreign exchange markets. Third, the gamma value of the Panel model is statistically significant but slight. We can conclude that nominal exchange rates and real exchange rates exist relationship in long terms but not in short terms. Fourth, the forecast abilities of two models are almost better than random walk model.
目次 Table of Contents
1.續論...................................................................................07
1.1研究動機及目的...........................................................07
1.2研究流程.......................................................................09
1.3研究架構.......................................................................10
2相關理論基礎與文獻回顧................................................11
2.1相關文獻.......................................................................13
2.1.1平滑轉換自我回歸模型(STAR)............................14
2.1.2多制度平滑轉換自我回歸模型(MRSTAR) .........15
2.1.3結構改變-平滑轉換自我回歸模型(TVSTAR) .....16
2.2國外文獻部分...............................................................17
2.3國內文獻部分...............................................................18
3個別國家模型....................................................................20
3.1估計參數及係數...........................................................22
3.2診斷性檢定...................................................................24
3.2.1檢定誤差是否存在自我相關.................................26
3.2.2檢定模型是否需要修正為MRSTAR模型.............27
3.2.3檢定模型是否需要修正為TVSTAR模型..............28
3.3預測...............................................................................29
4追蹤資料模型....................................................................31
4.1估計參數及係數...........................................................32
4.2診斷性檢定...................................................................33
4.2.1檢定模型是否需要修正為MRSTAR模型.............35
4.2.2檢定模型是否需要修正為TVSTAR模型..............36
4.3預測...............................................................................38
5實證結果與分析................................................................40
5.1數據來源.......................................................................40
5.2個別國家模型...............................................................41
5.3追蹤資料模型...............................................................49
6結論與建議........................................................................51
6.1結論...............................................................................51
6.2未來研究方向與建議...................................................52
參考文獻..............................................................................53
(表1)個別國家模型的BIC..................................................43
(表2)個別國家模型之參數和係數,即其標準差.............44
(表3)個別國家的誤差是否存在自我相關的檢定結果.....45
(表4)個別國家模型是否需要把模型修改成MRSTAR的檢
定結果.........................................................................46
(表5)個別國家模型是否需要把模型修改成TVSTAR的檢
定結果.........................................................................47
(表6)分別用兩模型預測後的RMSE結果..........................48
(表7)追蹤資料模型的估計結果.........................................49
(表8)追蹤資料模型是否需要把模型修改成MRSTAR的檢
定結果.........................................................................50
(表9)追蹤資料模型是否需要把模型修改成TVSTAR的檢
定結果.........................................................................50
(表10)分別用兩模型預測後的RMSE結果.......................50
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