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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/98904


    Title: 含外生多變數之TAR模型分析與預測
    Analysising and Forecasting for TAR Models with Exogenous Multi-Variables
    Authors: 陳致安
    Chen, Chih An
    Contributors: 吳柏林
    陳致安
    Chen, Chih An
    Keywords: 時間數列
    ARIMA
    外生變數
    TAR
    台股指數
    門檻值
    time series
    ARIMA
    exogenous variables
    TAR
    TAIEX index
    the threshold value
    Date: 2016
    Issue Date: 2016-07-11 17:42:27 (UTC+8)
    Abstract: 本研究使用含外生多變數為門檻值之TAR模型，分析並預測103年到105年的台股指數。建構多變量之門檻自迴歸模式較傳統以時變或自變數自動控制值更能反映出時間數列結構改變的過程與趨勢。這對於模式分析與預測有更優的解釋能力。且含外生多變數為門檻值之多變量門檻模式的可適用範圍很廣，尤其是當時間數列中的結構改變的現象，來自於外在多個變數衝擊，或非線性現象。此時加入多個外生變數作為考量，更能精準分析資料和做預測。我們以台股指數為例，實證結果顯示，我們所提出之模型，較傳統預測方法有更高之準確度。
    In this research, we use exogenous multi-variables as threshold values to construct a threshold autoregressive model in order to analysis and forecast TAIEX index between 103 years and 105 years. Constructing the threshold autoregressive model with multi-variables is better to reflect the process and trend of the change in time series structure than traditional model. This provides the better explanatory ability for model analysis and forecast. Also, the threshold autoregressive model with multi-variables containing exogenous multi-variables can apply more range, especially, as the structure change in time series due to the exogenous multi-variables shock. Through adding more exogenous variables, one can analyze data and forecast accurately. In this paper, the empirical results of TAIEX index shows that the threshold autoregressive model with multi-variables containing exogenous multi-variables is more precise than the traditional way.
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    Description: 碩士
    國立政治大學
    應用數學系
    102751016
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102751016
    Data Type: thesis
    Appears in Collections:[Department of Mathematical Sciences] Theses

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