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    ASIA unversity > 管理學院 > 財務金融學系 > 會議論文 >  Item 310904400/63744

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/63744

    Title: Estimating and Hedging Volatility of Stock Index Returns with the MIDAS-CARR Model
    Authors: David, K.Wangk;Chen, Yea-Mow
    Contributors: National University of Kaohsiung;National University of Kaohsiung
    Keywords: Volatility;GARCH;CARR;MIDAS;High/low range
    Date: 2013/3/1
    Issue Date: 2013-08-07 09:32:37 (UTC+8)
    Publisher: National University of Kaohsiung;National University of Kaohsiung
    Abstract: This paper uses the Mixed Data Sampling (MIDAS) and the Rolling Window (RW) methods to introduce conditional volatility into the CARR-family models. An augmented CARR model is shown to exhibit the advantages of both range-based volatility and high-frequency data in superior forecasting ability of volatility as compared to the GARCH models. Specifically, using the S&P500 stock index data, we find that the augmented CARR models (MIDAS-CARR and RW-CARR) are increasing the goodness of fit of the models and performing better in in-sample forecasting capability as compared to the GARCH and CARR models. This conclusion holds even with the existence of a structural change on the volatility. The augmented CARR models are also tested for out-of-sample forecasting ability, evaluated with RMSE and MAE statistics. We find that the CARR model is performing better than the GARCH model, and the MIDAS-CARR model and RW-CARR model are also performing better than the CARR model.
    Relation: 2013中部學術財金研討會 論文發表
    Appears in Collections:[財務金融學系] 會議論文

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