Estimation of High-Frequency Volatility: An Autoregressive Conditional Duration Approach
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.
Volume (Year): 30 (2012)
Issue (Month): 4 (April)
|Contact details of provider:|| Web page: http://www.tandfonline.com/UBES20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/UBES20|
When requesting a correction, please mention this item's handle: RePEc:taf:jnlbes:v:30:y:2012:i:4:p:533-545. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst)
If references are entirely missing, you can add them using this form.