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    題名: 長記憶分析
    Long Memory Analysis: An Empirical Investigation
    作者: 蔡易群
    貢獻者: 山本竜市
    Ryuichi Yamamoto
    蔡易群
    關鍵詞: 長記憶
    日期: 2012
    上傳時間: 2013-09-02 15:17:57 (UTC+8)
    摘要: 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。
    參考文獻: 5. References
    Baillie, R.T., Bollerslev, T., Mikkenlsen, H.O. 1996. Fractionally Intergrated Generalized Auroregressive Conditional Heteroskedaticity. Journal of Econometrics 74, PP. 3-30.
    Barkoulas, J.T., Baum, C.F., Travlos, N. 2000. Long Memory in the Greek Stock Market. Applied Financial Economics, 10, 177-184.
    Burton G.M. 1987. Efficient Market Hypothesis: The New Palgrave. A dictionary of Economics 2, PP. 120-23.
    Chordia, T., Roll, R., Subrahmanyam, A. 2008. Liquidity and Market Efficiency. Journal of Econometrics 87, PP.249-268.
    Chuang, W.I., Liu, H.H., Susmel, R. 2012. The bivirate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility. Global Finance Journal, In Press, Available Online 13, Elsevier.
    Conrad, C. 2010. Non-Negativity Conditions for the Hyperbolic GARCH Model. Journal of Econometrics 157, PP. 441_457.
    Ding, Z., Granger, C.W.J., Engle, R.F., 1993. A Long Memory Property of Stock Market Returns amd a New Model. Journal of Empirical Finance, PP83-106.
    Gourdazi, H. 2010. Modeling Long Memory in the Indian Stock Market using Fractional Integrated Egarch Model. International Journal of Trade, Economic and Finance, Vol. 1, No. 3, PP. 231-237
    Gewek, J., Porter-Hudak, S. 1983. The Estimation and Application of Long Memory Time Series Models. Journal of Times Series Analysis 4, PP. 221-238.
    Granger, C. W. J. 1980. Long Memory Relationships and the Aggregation of Dynamic Models. Journal of Econometrics, 14, PP. 227-238.
    Granger, C. W. J., Joyeux, R. 1980. An introduction to long memory time series model and fractional differencing. Journal of Time Series Analysis, No 1, PP. 15-29.
    Hosking, J. R. M. 1981. Fractional Differencing. Biometrica, 68, 165-176.
    Lee, J., Kim, T.S., Lee, H.K. 2000. Long Memory in Volatility of Korean Stock Market Returns. Available Online.
    Maheu, J.M. 2002. Can GARCH Models Capture the Long-range Dependence in Financial Market Volatility. Studies in Nonlinear Dynamics and Econometrics, 9(4), PP. 1-41.
    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.
    Nazarian, R., Naderi, E., Alikhani N.G., Amiri, A. 2013. Long Memory Analysis: An Empirical Investigation. MPRA, No. 45605.
    Poon, H., Granger, C.W.J. 2003. Forecasting Volatility in Financial Markets: A Review Journal of Economic Literature XLI, PP. 478-539.
    Vacha, L., Vosvrda, M.S. 2005. Dynamical Agent’s Strategies and the Fractal Market Hypothesis. Prague Economic Papers, No 2, PP. 163-170.
    Xiu, J., Jin, Y. 2007. Empirical Study of ARFIMA Model Based on Fractional Differencing. Physia: A 377, PP. 137-184.
    描述: 碩士
    國立政治大學
    國際經營與貿易研究所
    100351021
    101
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0100351021
    資料類型: thesis
    顯示於類別:[國際經營與貿易學系 ] 學位論文

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