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Article: Testing range estimators of historical volatility

TitleTesting range estimators of historical volatility
Authors
Issue Date2006
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0270-7314/
Citation
Journal Of Futures Markets, 2006, v. 26 n. 3, p. 297-313 How to Cite?
AbstractThis study investigates the relative performance of various historical volatility estimators that incorporate daily trading range: M. Parkinson (1980), M. Garman and M. Klass (1980), L. C. G. Rogers and S. E. Satchell (1991), and D. Yang and Q. Zhang (2000). It is found that the range estimators all perform very well when an asset price follows a continuous geometric Brownian motion. However, significant differences among various range estimators are detected if the asset return distribution involves an opening jump or a large drift. By adding microstructure noise to the Monte Carlo simulation, the finding of S. Alizadeh, M. W. Brandt, and F. X. Diebold (2002) - that range estimators are fairly robust toward microstructure effects - is confirmed. An empirical test with S&P 500 index return data shows that the variances estimated with range estimators are quite close to the daily integrated variance. The empirical results support the use of range estimators for actual market data. © 2006 Wiley Periodicals, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/85538
ISSN
2015 Impact Factor: 0.698
2015 SCImago Journal Rankings: 0.520
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorShu, Jen_HK
dc.contributor.authorZhang, JEen_HK
dc.date.accessioned2010-09-06T09:06:19Z-
dc.date.available2010-09-06T09:06:19Z-
dc.date.issued2006en_HK
dc.identifier.citationJournal Of Futures Markets, 2006, v. 26 n. 3, p. 297-313en_HK
dc.identifier.issn0270-7314en_HK
dc.identifier.urihttp://hdl.handle.net/10722/85538-
dc.description.abstractThis study investigates the relative performance of various historical volatility estimators that incorporate daily trading range: M. Parkinson (1980), M. Garman and M. Klass (1980), L. C. G. Rogers and S. E. Satchell (1991), and D. Yang and Q. Zhang (2000). It is found that the range estimators all perform very well when an asset price follows a continuous geometric Brownian motion. However, significant differences among various range estimators are detected if the asset return distribution involves an opening jump or a large drift. By adding microstructure noise to the Monte Carlo simulation, the finding of S. Alizadeh, M. W. Brandt, and F. X. Diebold (2002) - that range estimators are fairly robust toward microstructure effects - is confirmed. An empirical test with S&P 500 index return data shows that the variances estimated with range estimators are quite close to the daily integrated variance. The empirical results support the use of range estimators for actual market data. © 2006 Wiley Periodicals, Inc.en_HK
dc.languageengen_HK
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0270-7314/en_HK
dc.relation.ispartofJournal of Futures Marketsen_HK
dc.rightsThe Journal of Futures Markets. Copyright © John Wiley & Sons, Inc.en_HK
dc.titleTesting range estimators of historical volatilityen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0270-7314&volume=26&issue=3&spage=297&epage=313&date=2006&atitle=Testing+Range+Estimators+of+Historical+Volatilityen_HK
dc.identifier.emailZhang, JE: jinzhang@hku.hken_HK
dc.identifier.authorityZhang, JE=rp01125en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/fut.20197en_HK
dc.identifier.scopuseid_2-s2.0-32644450808en_HK
dc.identifier.hkuros117274en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-32644450808&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume26en_HK
dc.identifier.issue3en_HK
dc.identifier.spage297en_HK
dc.identifier.epage313en_HK
dc.identifier.isiWOS:000234980200004-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridShu, J=12243627100en_HK
dc.identifier.scopusauthoridZhang, JE=7601346659en_HK

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