Estimation of high-frequency volatility: An autoregressive conditional duration approach

• Main Authors: TSE, Yiu Kuen, YANG, Thomas Tao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: Market microstructure; Realized volatility; Semiparametric method; Transaction data; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1410; https://ink.library.smu.edu.sg/context/soe_research/article/2409/viewcontent/Estimation_of_High_Frequency_Volatility_2012.pdf
• Institution: Singapore Management University

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.