Correcting Intraday Periodicity Bias in Realized Volatility Measures

Dette, H. and Golosnoy, V. and Kellermann, J.

Volume: Pages:
DOI: 10.1016/j.ecosta.2021.03.002
Published: 2021

Diurnal fluctuations in volatility are a well-documented stylized fact of intraday price data. This warrants an investigation how this intraday periodicity (IP) affects both finite sample as well as asymptotic properties of several popular realized estimators of daily integrated volatility which are based on functionals of a finite number of intraday returns. It turns out that most of the estimators considered in this study exhibit a finite-sample bias due to IP, which can however get negligible when the number of intraday returns diverges to infinity. The appropriate correction factors for this bias are derived based on estimates of the IP. The adequacy of the new corrections is evaluated by means of a Monte Carlo simulation study and an empirical example. © 2021 EcoSta Econometrics and Statistics

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