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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/24416

    Title: Modeling asian stock returns with a more general parametric GARCH specification
    Other Titles: 一個新的參數化GARCH模型在亞洲股市上的應用
    Authors: 王凱立;Wang, Kai-li
    Contributors: 淡江大學國際貿易學系暨國際企業研究所
    Keywords: GARCH;skewness;high peakedness;kurtosis;forecasting;asymmetric;persistent
    Date: 2001-12-01
    Issue Date: 2009-11-30 18:21:03 (UTC+8)
    Publisher: 臺灣財務金融學會
    Abstract: High frequency stock return data tend to exhibit characteristics such as volatility clustering, volatility persistence, leverage effects, and properties of nonnormal unconditional distributions reflected in the form of skewness, high peakedness, and excess kurtosis. Although traditional GARCH models that employ leptokurtic distributions have been found useful to account for the conditional heteroscedasticity and leptokurtosis, they have difficulty in accommodating other stylized effects commonly observed in high frequency data. This paper attempts to rectify this deficiency by introducing a more general GJR IGARCH-EGB2 model, which not only considers the flexible distributional characteristics associated with the exponential beta distribution, but also incorporates the asymmetric conditional variance and integrated GARCH process into model consideration. Likelihood ratio tests, goodness of fit tests, distribution plots, and out-of-sample forecasts generate a preponderance of evidence to support the innovative GJR IGARCH-EGB2 specification over conventional competing alternatives presented in the literature.
    Relation: 財務金融學刊9(3),頁21-52
    DOI: 10.6545/JFS.2001.9(3).2
    Appears in Collections:[國際企業學系暨研究所] 期刊論文

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