Estimating Quadratic Variation Consistently in the Presence of Correlated Measurement Error
Ilze Kalnina and Oliver Linton
Published October 2006
We propose an econometric model that captures the e?ects of market microstructure on a latent price process. In particular, we allow for correlation between the measurement error and the return process and we allow the measurement error process to have a diurnal heteroskedasticity. We propose a modification of the TSRV estimator of quadratic variation. We show that this estimator is consistent, with a rate of convergence that depends on the size of the measurement error, but is no worse than n1=6. We investigate in simulation experiments the finite sample performance of various proposed implementations.
Paper Number EM/2006/509:
Download PDF - Estimating Quadratic Variation Consistently in the Presence of Correlated Measurement Error
JEL Classification: C12