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

Shouwei Liu Author Email: and Yiu-Kuen Tse Author Email:yktse@smu.edu.sg
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Shouwei Liu Author Email:: School of Economics, Singapore Management University
Yiu-Kuen Tse Author Email:yktse@smu.edu.sg: School of Economics, Singapore Management University

Working Papers from Singapore Management University, Sim Kee Boon Institute for Financial Economics

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.

Keywords: Autoregressive conditional duration; generalized autoregressive conditional heteroskedas-ticity; market microstructure; realized volatility; transaction data (search for similar items in EconPapers)
JEL-codes: C41 G12 (search for similar items in EconPapers)
Pages: 24 Pages
Date: 2012-02
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