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Article: The Autoregressive Conditional Marked Duration Model: Statistical Inference to Market Microstructure

TitleThe Autoregressive Conditional Marked Duration Model: Statistical Inference to Market Microstructure
Authors
KeywordsAutoregressive conditional duration
Likelihood ratio test
Market microstructure
Statistical inference
Issue Date2009
PublisherColumbia University, Department of Statistics. The Journal's web site is located at http://www.jds-online.com/
Citation
Journal of Data Science, 2009, v. 7, p. 189-201 How to Cite?
AbstractAbstract: We consider the Autoregressive Conditional Marked Duration (ACMD) model and apply it to 16 stocks traded in Hong Kong Stock Exchange (SEHK). By examining the orderings of appropriate sets of model parameters, market microstructure phenomena can be explained. To substantiate these conclusions, likelihood ratio test is used for testing the significance of the parameter orderings of the ACMD model. While some of our results resolve a few controversial market microstructure hypotheses and echo some of the existing empirical evidence, we discover some interesting market microstructure phenomena that may be characteristic to SEHK.
Persistent Identifierhttp://hdl.handle.net/10722/59864
ISSN

 

DC FieldValueLanguage
dc.contributor.authorKwok, SSMen_HK
dc.contributor.authorLi, WKen_HK
dc.contributor.authorYu, PLHen_HK
dc.date.accessioned2010-05-31T03:59:01Z-
dc.date.available2010-05-31T03:59:01Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal of Data Science, 2009, v. 7, p. 189-201en_HK
dc.identifier.issn1680-743Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/59864-
dc.description.abstractAbstract: We consider the Autoregressive Conditional Marked Duration (ACMD) model and apply it to 16 stocks traded in Hong Kong Stock Exchange (SEHK). By examining the orderings of appropriate sets of model parameters, market microstructure phenomena can be explained. To substantiate these conclusions, likelihood ratio test is used for testing the significance of the parameter orderings of the ACMD model. While some of our results resolve a few controversial market microstructure hypotheses and echo some of the existing empirical evidence, we discover some interesting market microstructure phenomena that may be characteristic to SEHK.-
dc.languageengen_HK
dc.publisherColumbia University, Department of Statistics. The Journal's web site is located at http://www.jds-online.com/en_HK
dc.relation.ispartofJournal of Data Scienceen_HK
dc.subjectAutoregressive conditional duration-
dc.subjectLikelihood ratio test-
dc.subjectMarket microstructure-
dc.subjectStatistical inference-
dc.titleThe Autoregressive Conditional Marked Duration Model: Statistical Inference to Market Microstructureen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1680-743X&volume=7&spage=189&epage=201&date=2009&atitle=The+Autoregressive+Conditional+Marked+Duration+Model:+Statistical+Inference+to+Market+Microstructureen_HK
dc.identifier.emailKwok, SSM: h0150920@hkusua.hku.hken_HK
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hken_HK
dc.identifier.emailYu, PLH: plhyu@hkucc.hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.identifier.authorityYu, PLH=rp00835en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros162549en_HK
dc.identifier.volume7-
dc.identifier.spage189-
dc.identifier.epage201-
dc.publisher.placeUnited States-

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