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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/54311


    Title: 匯率報酬模型之非線性調整及可預測性
    Nonlinear adjustment and predictability of exchange rate returns models
    Authors: 陳紹珍
    Contributors: 廖四郎
    陳紹珍
    Keywords: 匯率預測
    時間序列
    倒傳遞類神經網路
    非線性調整
    Exchange Rate Forecasting
    Time Series
    Back-propagation Neural Network
    Nonlinear Adjustment
    Date: 2011
    Issue Date: 2012-10-30 10:42:23 (UTC+8)
    Abstract: 在全球經貿體系自由化下，國際資金流通快速，匯率變動也非常頻繁，廠商的產銷決策與營運，面對匯率風險更加難以掌控。如何掌握匯率的變動，並採取有效的避險措施，是廠商從事貿易必須面臨之重要課題。本研究採用自我迴歸整合移動平均模式、倒傳遞類神經網路及混合式自我迴歸整合移動平均模式及倒傳遞類神經網路模型進行未來即期匯率報酬率之預測。試圖找出合適的新台幣兌美元即期匯率之預測模型，並將其應用於外匯避險操作。
    研究結果顯示，關於預測誤差的績效表現，整體來說，以自我迴歸整合移動平均及倒傳遞類神經網路混合式模型表現最佳，顯示傳統時間序列模型捕捉匯率報酬率走勢之能力，藉由倒傳遞類神經網路捕捉其線性預測誤差中非線性的部分，可更符合資料的特性，加強匯率報酬率預測的準確性。考慮預測方向的正確性，在兩個不同的準則下(SR、PT)，皆以自我迴歸整合移動平均模型表現最差，代表其在進行匯率報酬率之預測時正確率較為不足。而在PT檢定當中，倒傳遞類神經網路模型及混合式模型皆達到顯著。因此利用人工智慧模型對報酬率之方向進行預測是有效的，又以自我迴歸整合移動平均及倒傳遞類神經網路混合式模型表現最好。總結來說，利用倒傳遞類神經網路模型針對自我迴歸整合移動平均模型做非線性的調整，同時涵蓋未來匯率報酬率線性與非線性的部分，使得自我迴歸整合移動平均模型之預測誤差、方向準確性皆得到改善，藉由倒傳遞類神經網路捕捉其線性預測誤差中非線性的部分，可更符合資料的特性，加強匯率報酬率預測的準確性。
    Reference: 李志宏(1996)，「倒傳遞類神經網路與自我迴歸整合移動平均、計量分析及遠期匯率模式在匯率預測績效上之比較」，成功大學會計研究所碩士論文。
    邱至中(2003)，「長短期匯率預測模式績效之比較」，國立成功大學財務金融研究所碩士論文。
    周宗南、劉瑞鑫(2005)，「演化式類神經網路應用於台股指數報酬率之預測」，財金論文叢刊，第三期，77-94。
    陳學毅(2004)，「匯率預測模型績效之研究—時間序列及灰色預測模型之應用」，東海大學國際貿易研究所碩士論文。
    Al-Alawi, S. M., Abdul-Wahab, S. A. and Bakheit, C. S.(2008), “Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone,” Enviromental Modeling and Software, 23, 396-403.
    Chiang, Y. C., Liao, T. L. and Hsiao, T. A. (2011), “Evaluating hedging strategies in the foreign exchange market with the stochastic dominance approach,” Applied Financial Economics, 21, 493-503.
    Eaker, M. R. and Grant, D. M. (1990), “Currency hedging strategies for internationally diversified equity portfolios,” Journal of Portfolio Management, 17, 30-32.
    Fang, H and Kwong, k. k. (1991), “Forecasting Foreign Exchange Rate,” Journal of Business Forecasting, 16-19.
    Hazuka, T. B. and Huberts, L. C. (1994), “A valuation approach to currency hedging, ” Financial Analysts Journal, 50, 55-59.
    Jeong, J. G.(2000), “What drives exchange rate: the case of the yen/dollar rate,” Multinational Business Review, 8, 31-36.
    Leung, M. T.(2000), “Forecasting Exchange Rates Using General Regression Neural Networks,” Computers and Operations Research, Volume 27, Issues 11-12,1093-1110.
    MacDonald, R. (1998), “What determines real exchange rate? The long and the short of it,” Journal of Financial Markets, Institutions and money, 8, 117-153.
    Morey, M. R. and Simpson , M. W.(2001), “To hedge or not to hedge: The performance of simple strategies for hedging foreign exchange rate risk,” Journal of Multinational Financial Management, 11, 213-223.
    Preminger, A. and Franck, R. (2007), “Forecasting Exchange rates: A Robust Regression Approach,” International Journal of Forecasting, Volume 23, Issue 1, 71-84.
    Simpson, M. W. and Dania, A. (2006), “ Selective hedging the euro,” Journal of Multinational Financial Management, 16, 27-42.
    VanderLinden, D., Jiang, C. X. and Hu, M. (2002), “Conditional hedging and portfolio performance,” Financial Analysts Journal, 58, 72-82.
    Description: 碩士
    國立政治大學
    金融研究所
    99352005
    100
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099352005
    Data Type: thesis
    Appears in Collections:[Department of Money and Banking] Theses

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