This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise.  We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation...

In this paper we present the central limit theorem for general functions of the increments of Brownian semimartingales. This provides a natural extension of the results derived in Barndorff-Nielsen, Graversen, Jacod, Podolskij and Shephard (2006), who showed the central limit theorem for even...

We consider kernel-based estimators of integrated variances in the presence of independent market microstructure effects. We derive the bias and variance properties for all regular kernel-based estimators and derive a lower bound for their asymptotic variance. Further we show that the...

Estimating the covariance and correlation between assets using high frequency data is challenging due to market microstructure effects and Epps effects.  In this paper we extend Xiu's univariate QML approach to the multivariate case, carrying out inference as if the observations arise from an...

High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps.  One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to...

Financial assets` quoted prices normally change through frequent revisions, or jumps. For markets where quotes are almost always revised by the minimum price tick, this paper proposes a new estimator of Quadratic Variation which is robust to microstructure effects. It compares the number of...

For financial assets whose best quotes almost always change by jumping by the market`s price tick size (one cent, five cents, etc.), this paper proposes an estimator of Quadratic Variation which controls for microstructure effects. It measures the prevalence of alternations, where quotes jump...