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Estimating quadratic variation consistently in the presence of correlated measurement error

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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.

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en

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application/pdf

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http://eprints.lse.ac.uk/4413/1/Estimating_Quadratic_Variation_Consistently_in_the_Presence_of_Correlated_Measurement_Error.pdf

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