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.

波动的日波动是日内价格数据的一个有据可查的程式化事实。这值得研究这种日内周期性 (IP) 如何影响有限样本以及基于有限数量日内收益的函数的几种流行的每日综合波动率已实现估计量的渐近特性。事实证明，本研究中考虑的大多数估计量都表现出由于 IP 导致的有限样本偏差，但是当日内收益的数量发散到无穷大时，这种偏差可以忽略不计。这种偏差的适当校正因子是根据 IP 的估计得出的。新修正的充分性通过蒙特卡洛模拟研究和经验示例进行评估。