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Estimation of High-Frequency Volatility: An Autoregressive Conditional Duration Approach

Listed author(s):
  • Yiu-kuen Tse
  • Thomas Tao Yang
Registered author(s):

    We propose a method to estimate the intraday volatility of a stock by integrating the instantaneous conditional return variance per unit time obtained from the autoregressive conditional duration (ACD) model, called the ACD-ICV method. We compare the daily volatility estimated using the ACD-ICV method against several versions of the realized volatility (RV) method, including the bipower variation RV with subsampling, the realized kernel estimate, and the duration-based RV. Our Monte Carlo results show that the ACD-ICV method has lower root mean-squared error than the RV methods in almost all cases considered. This article has online supplementary material.

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    Article provided by Taylor & Francis Journals in its journal Journal of Business & Economic Statistics.

    Volume (Year): 30 (2012)
    Issue (Month): 4 (April)
    Pages: 533-545

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    Handle: RePEc:taf:jnlbes:v:30:y:2012:i:4:p:533-545
    DOI: 10.1080/07350015.2012.707582
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