Stationary bootstrapping realized volatility under market microstructure noise

Abstract

Large-sample validity is proved for stationary bootstrapping of a bias-corrected realized volatility under market microstructure noise, which enables us to construct a bootstrap confidence interval of integrated volatility. A finite-sample simulation shows that the stationary bootstrapping confidence interval outperforms existing ones which are constructed ignoring market microstructure noise or using asymptotic normality for the bias-corrected realized volatility.