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Estimation of Monthly Volatility: An Empirical Comparison of Realized Volatility, GARCH and ACD-ICV Methods

Author

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  • Shouwei Liu

    (School of Economics, Singapore Management University)

  • Yiu-Kuen Tse

    (School of Economics, Singapore Management University)

Abstract

We apply the ACD-ICV method proposed by Tse and Yang (2011) for the estimation of intraday volatility to estimate monthly volatility, and empirically compare this method against the re- alized volatility (RV) and generalized autoregressive conditional heteroskedasticity (GARCH) methods. Our Monte Carlo results show that the ACD-ICV method performs well against the other two meth- ods. Evidence on the Chicago Board Options Exchange volatility index (VIX) shows that it predicts the ACD-ICV volatility estimates better than it predicts the RV estimates. While the RV method is popular for the estimation of monthly volatility, its performance is inferior to the GARCH method.

Suggested Citation

  • Shouwei Liu & Yiu-Kuen Tse, 2012. "Estimation of Monthly Volatility: An Empirical Comparison of Realized Volatility, GARCH and ACD-ICV Methods," Working Papers CoFie-01-2012, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    • Handle: RePEc:skb:wpaper:cofie-01-2012
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    More about this item

    Keywords

    Autoregressive conditional duration; generalized autoregressive conditional heteroskedas-ticity; market microstructure; realized volatility; transaction data;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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