Time endogeneity and an optimal weight function in pre-averaging covariance estimation

Yuta Koike ()
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Yuta Koike: The Institute of Statistical Mathematics

Statistical Inference for Stochastic Processes, 2017, vol. 20, issue 1, No 2, 15-56

Abstract: Abstract We establish a central limit theorem for a class of pre-averaging covariance estimators in a general endogenous time setting. In particular, we show that the time endogeneity has no impact on the asymptotic distribution if certain functionals of observation times are asymptotically well-defined. This contrasts with the case of the realized volatility in a pure diffusion setting. We also discuss an optimal choice of the weight function in the pre-averaging.

Keywords: Central limit theorem; Jumps; Market microstructure noise; Non-synchronous observations; Pre-averaging; Time endogeneity (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11203-016-9135-3

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