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    ASIA unversity > 管理學院 > 財務金融學系 > 期刊論文 >  Item 310904400/17594

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/17594

    Title: The Efficacy of Model-Based Volatility Forecasting: Empirical Evidence in Taiwan
    Authors: 臧仕維;Tzang, Shyh-Weir;Chih-Hsing Hung;So-De Hsyu
    Contributors: 財務金融學系
    Keywords: Realized volatility;range volatility;semiparametric fractional autoregressive model;multiplicative error model;GJR-GARCH model;variance gamma garch model
    Date: 2009-04
    Issue Date: 2012-11-26 10:37:31 (UTC+8)
    Abstract: The paper adopts several time series models to assess the forecasting efficiency of future realized volatility in Taiwan stock market. The paper finds that, for 1-day directional accuracy forecast performance, semiparametric fractional autoregressive model (SEMIFAR, Beran and Ocker, 2001) ranks highest with 78.52% hit accuracy, followed by multiplicative error model (MEM, Engle, 2002), and augmented GJR-GARCH model. For 1-day forecasting errors evaluated by root mean squared errors (RMSE), GJR-GARCH model augmented with high-low range volatility ranks the highest, followed by SEMIFAR and MEM model, both of which, however, outperform augmented GJR-GARCH by the measure of mean absolute value (MAE) and p-statistics (Blair, Poon and Taylor, 2001).
    Relation: International Research Journal of Finance and Economics
    Appears in Collections:[財務金融學系] 期刊論文

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