Estimating the integrated volatility with tick observations

Jean Jacod, Yingying Li and Xinghua Zheng

Journal of Econometrics, 2019, vol. 208, issue 1, 80-100

Abstract: We develop a volatility estimator that can be directly applied to tick-by- tick data. More specifically, we consider a model that allows for (i) irregular observation times that can be endogenous, (ii) dependent noise that can have diurnal features and be dependent on the latent price process, and (iii) jumps in the latent price process. We show that our estimator yields consistent estimates and enjoys the optimal rate of convergence. Simulation as well as empirical studies demonstrate favorable properties of our proposed estimator.

Keywords: High frequency data; Integrated volatility; Market microstructure noise; Dependent noise; Endogenous time (search for similar items in EconPapers)
JEL-codes: C13 C14 D40 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:208:y:2019:i:1:p:80-100

DOI: 10.1016/j.jeconom.2018.09.006

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