Estimating quadratic variation consistently in the presence of correlated measurement error
Ilze Kalnina and
Oliver Linton ()
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
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.
Keywords: Endogenous noise; Market Microstructure; Realised Volatility; Semimartingale (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Pages: 43 pages
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:4413
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