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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/59234


    Title: 長記憶分析
    Long Memory Analysis: An Empirical Investigation
    Authors: 蔡易群
    Contributors: 山本竜市
    Ryuichi Yamamoto
    蔡易群
    Keywords: 長記憶
    Date: 2012
    Issue Date: 2013-09-02 15:17:57 (UTC+8)
    Abstract: 本研究欲藉由結合ARFIMA及FIGARCH兩模型來試圖去捕捉長記憶現象。首先,本研究將簡單回顧兩模型之相關理論與應用,再介紹在實務上廣泛被運用之長記憶現象之相關檢定。ARFIMA及FIGARCH模型中詮釋長記憶現在之分型係數d,分別使得模型在描述與預估金融時間序列之報酬及波動性的表現上相當突出。
    本研究所研究之對象為日本股市,所使用的資料為日經225指數。實證結果顯示,日報酬中含條件異質性變異數之現象。在模型的選擇上,本研究預估及比較了許多不同的模型,並且確認了長記憶確實存在於報酬及波動,以及最適之模型為ARFIMA-FIGARCH。
    Reference: 5. References
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    Mun, M., Brooks, R. 2012. The roles of news and volatility in stock market correlations during the global financial crisis. Emerging Markets Review 13(1), PP. 1-7.
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    Description: 碩士
    國立政治大學
    國際經營與貿易研究所
    100351021
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0100351021
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

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