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題名 截取式自迴歸條件變異數分析法
Trimmed ARCH(1) model
作者 廖本杰
貢獻者 吳柏林
廖本杰
關鍵詞 非線性時間數列
模糊熵分類
轉折區間
截取點
Non-linear time series
Fuzzy classification
Structure changed period
Cut point
日期 1996
上傳時間 28-四月-2016 09:56:07 (UTC+8)
摘要 時間數列分析過程,常常發現其走勢,隨著時間過程而演變,應用傳統的線性模式來配適,往往很難獲得合適預測值。因此近幾年來,非線性時間數列結構性改變的研究越來越受到重視,也一直是時間數列及計量經濟學學者所熱衷的研究主題之一。本文利用模糊理論的觀念,以模糊炳找出配適ARCH模式數列之轉折區間,分別以轉折區問起始點及結束點作為截取點,去配適ARCH(1)模式,稱之為截取式自迴歸條件變異數分析法(Trimmed ARCH(1) model)。針對台幣對美元銀行間每日收盤匯率,分別以單變量ARIMA、ARCH(1)、Trtmmed ARCH(1)來建構模式,並做比較分析。比較結果發現,以轉折區間結束點作為截取點之Trimmed ARCH(1)模式,其預測值最為準確,大為改善了原來ARCH(1)模式之預測水準。
In time series analysis, we often find the trend of which changing with time. Using the traditional model fitting can`t get a good prediction. Hence the research of structure change of non-linear time series is attentive in recent years, and non-linear time series analysis is a research topic which the scholars of time series and econometrics are intent on. This article tries to use the theory of fuzzy ,to recognize the structure change period by the fuzzy classification, let the first point and the last point of the structure change period be the cute points, to fit ARCH(1) mod ie which we called the Trimmed ARCH(1) model. We use the data of the exchange rate between N.T dol liars and U.S dollars to compare the ARIMAwith ARCH(1) and Trimmed ARCH(1), the forcasting performance shows that Trimmed ARCH(1) model takes a better prediction result.
描述 碩士
國立政治大學
應用數學系
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002002527
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.author (作者) 廖本杰zh_TW
dc.creator (作者) 廖本杰zh_TW
dc.date (日期) 1996en_US
dc.date.accessioned 28-四月-2016 09:56:07 (UTC+8)-
dc.date.available 28-四月-2016 09:56:07 (UTC+8)-
dc.date.issued (上傳時間) 28-四月-2016 09:56:07 (UTC+8)-
dc.identifier (其他 識別碼) B2002002527en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/87111-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 應用數學系zh_TW
dc.description.abstract (摘要) 時間數列分析過程,常常發現其走勢,隨著時間過程而演變,應用傳統的線性模式來配適,往往很難獲得合適預測值。因此近幾年來,非線性時間數列結構性改變的研究越來越受到重視,也一直是時間數列及計量經濟學學者所熱衷的研究主題之一。本文利用模糊理論的觀念,以模糊炳找出配適ARCH模式數列之轉折區間,分別以轉折區問起始點及結束點作為截取點,去配適ARCH(1)模式,稱之為截取式自迴歸條件變異數分析法(Trimmed ARCH(1) model)。針對台幣對美元銀行間每日收盤匯率,分別以單變量ARIMA、ARCH(1)、Trtmmed ARCH(1)來建構模式,並做比較分析。比較結果發現,以轉折區間結束點作為截取點之Trimmed ARCH(1)模式,其預測值最為準確,大為改善了原來ARCH(1)模式之預測水準。zh_TW
dc.description.abstract (摘要) In time series analysis, we often find the trend of which changing with time. Using the traditional model fitting can`t get a good prediction. Hence the research of structure change of non-linear time series is attentive in recent years, and non-linear time series analysis is a research topic which the scholars of time series and econometrics are intent on. This article tries to use the theory of fuzzy ,to recognize the structure change period by the fuzzy classification, let the first point and the last point of the structure change period be the cute points, to fit ARCH(1) mod ie which we called the Trimmed ARCH(1) model. We use the data of the exchange rate between N.T dol liars and U.S dollars to compare the ARIMAwith ARCH(1) and Trimmed ARCH(1), the forcasting performance shows that Trimmed ARCH(1) model takes a better prediction result.en_US
dc.description.tableofcontents 1、前言-----1
     
     2、截取式自迴歸條件變異數分析法模型研究Trimmed ARCH(1) model
     2.1 ARCH(1)模型-----4
     2.2 截取點之決定-----5
     2.3 截取式自迴歸條件變異數分析法Trim-ARCH(1) model-----6
     
     3、模擬與比較
     3.1 資料模擬-----9
     3.2 配適ARCH(1)及Trimmed ARCH(1)模型-----11
     
     4、實證分析
     4.1 序列圖形識別與分析-----13
     4.2 ARMA模式之配適-----14
     4.3 截取點之選取-----17
     4.4 配適ARCH(1)及TrimARCH(1)模型-----19
     4.5 模式評估分與比較-----20
     
     5、結論與建議-----23
     
     參考書目-----25
     附錄1 實證分析之ACF與PACF圖-----27
     附錄2 ARCH(1)模型之程式-----28
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002002527en_US
dc.subject (關鍵詞) 非線性時間數列zh_TW
dc.subject (關鍵詞) 模糊熵分類zh_TW
dc.subject (關鍵詞) 轉折區間zh_TW
dc.subject (關鍵詞) 截取點zh_TW
dc.subject (關鍵詞) Non-linear time seriesen_US
dc.subject (關鍵詞) Fuzzy classificationen_US
dc.subject (關鍵詞) Structure changed perioden_US
dc.subject (關鍵詞) Cut pointen_US
dc.title (題名) 截取式自迴歸條件變異數分析法zh_TW
dc.title (題名) Trimmed ARCH(1) modelen_US
dc.type (資料類型) thesisen_US