Integrated Variance of Irregularly Spaced High-Frequency Data: A State Space Approach Based on Pre-Averaging

Alexeev, V; Chen, J; Ignatieva, K

Integrated Variance of Irregularly Spaced High-Frequency Data: A State Space Approach Based on Pre-Averaging

Alexeev, V Chen, J Ignatieva, K

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Publisher:: De Gruyter
Publication Type:: Journal Article
Citation:: Studies in Nonlinear Dynamics and Econometrics, 2023, 27, (5), pp. 733-763
Issue Date:: 2023

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Field	Value	Language
dc.contributor.author	Alexeev, V
dc.contributor.author	Chen, J
dc.contributor.author	Ignatieva, K
dc.date.accessioned	2024-01-08T01:06:36Z
dc.date.available	2024-01-08T01:06:36Z
dc.date.issued	2023
dc.identifier.citation	Studies in Nonlinear Dynamics and Econometrics, 2023, 27, (5), pp. 733-763
dc.identifier.issn	1081-1826
dc.identifier.issn	1558-3708
dc.identifier.uri	http://hdl.handle.net/10453/174076
dc.description.abstract	We propose a new state space model to estimate the Integrated Variance (IV) in the presence of microstructure noise. Applying the pre-averaging sampling scheme to the irregularly spaced high-frequency data, we derive equidistant efficient price approximations to calculate the noise-contaminated realised variance (NCRV), which is used as an IV estimator. The theoretical properties of the new volatility estimator are illustrated and compared with those of the realised volatility. We highlight the robustness of the new estimator to market microstructure noise (MMN). The pre-averaging sampling effectively eliminates the influence of the MMN component on the NCRV series. The empirical illustration features the EUR/USD exchange rate and provides evidence of a superior performance in volatility forecasting at very high sampling frequencies.
dc.language	English
dc.publisher	De Gruyter
dc.relation.ispartof	Studies in Nonlinear Dynamics and Econometrics
dc.relation.isbasedon	10.1515/snde-2021-0093
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 1403 Econometrics
dc.subject.classification	Econometrics
dc.subject.classification	3801 Applied economics
dc.subject.classification	3802 Econometrics
dc.title	Integrated Variance of Irregularly Spaced High-Frequency Data: A State Space Approach Based on Pre-Averaging
dc.type	Journal Article
utslib.citation.volume	27
utslib.for	0102 Applied Mathematics
utslib.for	1403 Econometrics
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2024-01-08T01:06:35Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	27
utslib.citation.issue	5

Abstract:

We propose a new state space model to estimate the Integrated Variance (IV) in the presence of microstructure noise. Applying the pre-averaging sampling scheme to the irregularly spaced high-frequency data, we derive equidistant efficient price approximations to calculate the noise-contaminated realised variance (NCRV), which is used as an IV estimator. The theoretical properties of the new volatility estimator are illustrated and compared with those of the realised volatility. We highlight the robustness of the new estimator to market microstructure noise (MMN). The pre-averaging sampling effectively eliminates the influence of the MMN component on the NCRV series. The empirical illustration features the EUR/USD exchange rate and provides evidence of a superior performance in volatility forecasting at very high sampling frequencies.

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http://hdl.handle.net/10453/174076