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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/67603


    Title: Beveridge-Nelson分解趨勢方法對匯率預測模型績效之影響 -以新台幣兌美元匯率為例
    The Influence of Exchange Rate Forecasting Model Performance on Beveridge-Nelson Decomposition Method-The Case of NTD/USD exchange rate.
    Authors: 紀筌惟
    Chi, Chuan Wei
    Contributors: 林建秀
    Lin, Chien Hsiu
    紀筌惟
    Chi, Chuan Wei
    Keywords: 匯率預測
    向量誤差修正模型
    BN分解
    Exchange rate forecasting
    Vector error correction model
    Beveridge-Nelson decompostion
    Date: 2013
    Issue Date: 2014-07-21 15:38:48 (UTC+8)
    Abstract: 本研究以新台幣兌美元之匯率日資料作為主要研究標的，同時加入台灣加權股價指數及金融業隔夜拆借利率之日資料作為股價與利率之代理變數，利用Beveridge-Nelson分解趨勢的方法將變數資料拆解成趨勢項與循環項之時間序列資料，藉此捕捉匯率資料具有景氣循環的特性。在循環項的序列資料，以向量自我迴歸模型來分析並予以估計，趨勢項的部分，利用共整合檢定來探討趨勢項變數間長期的均衡關係，再以向量誤差修正模型予以估計，得到未來30天期之匯率走勢。接著，再以RMSE與MAE指標來衡量不同模型之匯率預測績效，以期能找出最適之匯率預測模型。
    實證研究結果發現，將匯率資料先透過Beveridge-Nelson分解趨勢的方法予以拆解後，再利用時間序列模型進行分析及預測，時間序列模型的預測能力都比原始匯率利用時間序列模型進行預測或透過ARIMA模型進行預測還要來的好。因此，根據實證研究的結果，若企業與政府在進行匯率預測的分析時，能夠考慮先將匯率資料透過Beveridge-Nelson分解方法予以處理，便能更有效提升模型的預測能力，除了企業能夠降低避險成本來提高公司整體績效，對於國家而言，有效的掌握匯率的趨勢便能夠迅速且正確的制定政策，提升國家的經濟發展。
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    Description: 碩士
    國立政治大學
    金融研究所
    101352033
    102
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0101352033
    Data Type: thesis
    Appears in Collections:[Department of Money and Banking] Theses

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