Edgeworth expansions for realized volatility and related estimators

Lan Zhang; Per A. Mykland; Yacine At-Sahalia

doi:10.1016/j.jeconom.2010.03.030

Edgeworth expansions for realized volatility and related estimators

Lan Zhang, Per A. Mykland, Yacine At-Sahalia

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to CornishFisher inversion and help setting intervals more accurately than those relying on normal distribution.

Original language	English (US)
Pages (from-to)	190-203
Number of pages	14
Journal	Journal of Econometrics
Volume	160
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2010.03.030
State	Published - Jan 2011

All Science Journal Classification (ASJC) codes

Economics and Econometrics

Keywords

Bias correction
Edgeworth expansion
Market microstructure
Martingale
Realized volatility
Two scales realized volatility

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10.1016/j.jeconom.2010.03.030

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title = "Edgeworth expansions for realized volatility and related estimators",

abstract = "This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to CornishFisher inversion and help setting intervals more accurately than those relying on normal distribution.",

keywords = "Bias correction, Edgeworth expansion, Market microstructure, Martingale, Realized volatility, Two scales realized volatility",

author = "Lan Zhang and Mykland, {Per A.} and Yacine At-Sahalia",

note = "Funding Information: Financial support from the NSF under grants SBR-0350772 (A{\"i}t-Sahalia) and DMS-0204639, DMS 06-04758, and SES 06-31605 (Mykland and Zhang) is gratefully acknowledged. The authors would like to thank the editors and referees for helpful comments and suggestions. ",

year = "2011",

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doi = "10.1016/j.jeconom.2010.03.030",

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AU - Zhang, Lan

AU - Mykland, Per A.

AU - At-Sahalia, Yacine

N1 - Funding Information: Financial support from the NSF under grants SBR-0350772 (Aït-Sahalia) and DMS-0204639, DMS 06-04758, and SES 06-31605 (Mykland and Zhang) is gratefully acknowledged. The authors would like to thank the editors and referees for helpful comments and suggestions.

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N2 - This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to CornishFisher inversion and help setting intervals more accurately than those relying on normal distribution.

AB - This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we derive Edgeworth expansions for such estimators. The expansions are developed in the framework of small-noise asymptotics. The results have application to CornishFisher inversion and help setting intervals more accurately than those relying on normal distribution.

KW - Bias correction

KW - Edgeworth expansion

KW - Market microstructure

KW - Martingale

KW - Realized volatility

KW - Two scales realized volatility

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JO - Journal of Econometrics

JF - Journal of Econometrics

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Edgeworth expansions for realized volatility and related estimators

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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