Long memory in stock-market trading volume

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dc.contributor.author Ignacio, Lobato N.
dc.contributor.author Velasco, Carlos
dc.date.accessioned 2009-06-16T13:01:49Z
dc.date.available 2009-06-16T13:01:49Z
dc.date.issued 2000-10
dc.identifier.bibliographicCitation Journal of Business and Economic Statistics. 2000, vol. 18, nº 4, p. 410-427
dc.identifier.issn 0735-0015
dc.identifier.uri http://hdl.handle.net/10016/4433
dc.description.abstract This article examines consistent estimation of the long-memory parameters of stock-market trading volume and volatility. The analysis is carried out in the frequency domain by tapering the data instead of detrending them. The main theoretical contribution of the article is to prove a central limit theorem for a multivariate two-step estimator of the memory parameters of a nonstationary vector process. Using robust semiparametric procedures, the long-memory properties of trading volume for the 30 stocks in the Dow Jones Industrial Average index are analyzed. Two empirical results are found. First, there is strong evidence that stock-market trading volume exhibits long memory. Second, although it is found that volatility and volume exhibit the same degree of long memory for most of the stocks, there is no evidence that both processes share the same long-memory component.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher American Statistical Association
dc.rights © American Statistical Association
dc.subject.other Detrending
dc.subject.other Long-range dependence
dc.subject.other Nonstacionary processes
dc.subject.other Semiparametric inference
dc.subject.other Tapering
dc.subject.other Volatility
dc.title Long memory in stock-market trading volume
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://www.jstor.org/stable/1392223
dc.subject.eciencia Economía
dc.rights.accessRights openAccess
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