A powerful test for conditional heteroscedasticity for financial time series with highly persistent volatilities.

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dc.contributor.author Rodríguez, Julio
dc.contributor.author Ruiz, Esther
dc.date.accessioned 2012-11-02T13:04:48Z
dc.date.available 2012-11-02T13:04:48Z
dc.date.issued 2005
dc.identifier.bibliographicCitation Statistica Sinica, 2005, vol. 15, n. 2, p. 505-526
dc.identifier.issn 1017-0405
dc.identifier.uri http://hdl.handle.net/10016/4910
dc.description.abstract Traditional tests for conditional heteroscedasticity are based on testing for significant autocorrelations of squared or absolute observations. In the context of high frequency time series of financial returns, these autocorrelations are often positive and very persistent, although their magnitude is usually very small. Moreover, the sample autocorrelations are severely biased towards zero, especially if the volatility is highly persistent. Consequently, the power of the traditional tests is often very low. In this paper, we propose a new test that takes into account not only the magnitude of the sample autocorrelations but also possible patterns among them. This additional information makes the test more powerful in situations of empirical interest. The asymptotic distribution of the new statistic is derived and its finite sample properties are analyzed by means of Monte Carlo experiments. The performance of the new test is compared with various alternative tests. Finally, we illustrate the results analyzing several time series of financial returns.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.isversionof http://hdl.handle.net/10016/204
dc.subject.other GARCH
dc.subject.other Long-memory
dc.subject.other McLeod-Li statistic
dc.subject.other Stochastic volatility
dc.title A powerful test for conditional heteroscedasticity for financial time series with highly persistent volatilities.
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://www3.stat.sinica.edu.tw/statistica/J15N2/J15N211/J15N211.html
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 505
dc.identifier.publicationissue 2
dc.identifier.publicationlastpage 526
dc.identifier.publicationtitle Statistica Sinica
dc.identifier.publicationvolume 15
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