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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/31652

    Title: 原油價格波動性預測
    Other Titles: Forecasting the volatility of crude oil price
    Authors: 陳佳琪;Chen, Chia-chi
    Contributors: 淡江大學財務金融學系碩士班
    李命志;Lee, Ming-chih
    Keywords: 峰態;偏態;預測;GARCH;GJR;SGT;Leptokurtosis;Skewness;Forecasting
    Date: 2008
    Issue Date: 2010-01-11 01:05:58 (UTC+8)
    Abstract: 本文研究西德州原油日報酬的波動性,第一部分以對稱性的GARCH模型及波動不對稱的GJR─GARCH模型均架構於一般化誤差分配(GED)及常態分配進行比較,檢視何者為最佳波動性預測模型。實證結果顯示以西德州原油日報酬為研究標的時,GJR GARCH─GED模型的預測能力較佳。
    This research introduces the volatility of West Texas Intermediate daily return. In part one, in order to test which model is the best, we compared the differences among GARCH-Normal, GARCH-GED, GJR GARCH-Normal and GJR GARCH-GED model. The empirical results indicate that GJR GARCH-GED model can forecast the volatility of West Texas Interemdiate daily return well.
    In part two, the empirical results indicate that the predictive ability of SGT is much better than GT、ST、t and Normal distribution. SGT can correct not only fat-tailed property, but also defects the low kurtosis of GT and t distribution. For the volatility of asset return setting, the assumption of volatility of assets price is more appropriate than Normal and asymmetric distribution which was often used.
    Appears in Collections:[財務金融學系暨研究所] 學位論文

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