Edgeworth Expansions for Realized Volatility and Related Estimators

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

This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful terms, one needs to let the size of the noise to go zero asymptotically. The results have application to Cornish-Fisher inversion and bootstrapping

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Year of publication:	October 2005
Authors:	Zhang, Lan
Other Persons:	Mykland, Per A. (contributor) ; Ait-Sahalia, Yacine (contributor)
Institutions:	National Bureau of Economic Research (contributor)
Publisher:	Cambridge, Mass : National Bureau of Economic Research
Subject:	Zeitreihenanalyse \| Time series analysis \| Schätztheorie \| Estimation theory

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Extent:	1 Online-Ressource
Series:	NBER technical working paper series ; no. t0319
Type of publication:	Book / Working Paper
Language:	English
Notes:	Mode of access: World Wide Web System requirements: Adobe [Acrobat] Reader required for PDF files Hardcopy version available to institutional subscribers.
Other identifiers:	10.3386/t0319 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

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