Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error

We propose an econometric model that captures the effects 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 mod...

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Bibliographic Details
Published in:Econometrics 2008-11, Vol.147 (1), p.47-59
Main Authors: Kalnina, Ilze, Linton, Oliver
Format: Article
Language:English
Subjects:
Convergence
Correlation analysis
Econometrics
Endogenous noise
Endogenous noise Market microstructure Realised volatility Semimartingale
Error
Estimating techniques
Estimation
Market microstructure
Market structure
Measurement
Measurement errors
Realised volatility
Semimartingale
Simulation
Studies
Variance
Volatility
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Summary:We propose an econometric model that captures the effects 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 n − 1 / 6 . We investigate in simulation experiments the finite sample performance of various proposed implementations.
ISSN:0304-4076
2225-1146
1872-6895
2225-1146
DOI:10.1016/j.jeconom.2008.09.016