Efficient Estimation of Integrated Volatility Incorporating Trading Information

Abstract

We consider a setting where market microstructure noise is a parametric function of trading information, possibly with a remaining noise component. Assuming that the remaining noise is $O_p(1/\sqrt{n})$, allowing irregular times and jumps, we show that we can estimate the parameters at rate $n$, and propose a volatility estimator which enjoys $\sqrt{n}$ convergence rate. Simulation studies show that our method performs well even with model misspecification and rounding. Empirical studies demonstrate the practical relevance and advantages of our method. Furthermore, we find that a simple model can account for a high percentage of the total variation of the microstructure noise.

Keywords: High frequency data, integrated volatility, market microstructure noise, realized volatility, efficiency

JEL Classification: G12, C22, C14