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An Unbiased Measure of Integrated Volatility in the Frequency Domain
Author(s) -
Wang Fangfang
Publication year - 2016
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12137
Subject(s) - estimator , mathematics , volatility (finance) , econometrics , frequency domain , central limit theorem , bias of an estimator , realized variance , noise (video) , statistics , consistent estimator , market microstructure , variance (accounting) , minimum variance unbiased estimator , economics , computer science , mathematical analysis , finance , artificial intelligence , accounting , order (exchange) , image (mathematics)
This article studies the effect of market microstructure noise on volatility estimation in the frequency domain. We propose a bias‐corrected periodogram‐based estimator of integrated volatility. We show that the new estimator is consistent and the central limit theorem is established under a general assumption of the noise. We also provide a feasible procedure for computing the bias‐corrected estimator in practice. As a byproduct, we extract a consistent frequency‐domain estimator of the long‐run variance of market microstructure noise from high‐frequency data.