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Multivariate fractional integration tests allowing for conditional heteroskedasticity with an application to return volatility and trading volume

2021-08Artigo científico Acesso aberto
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dc.contributor.authorBalboa, Marina
dc.contributor.authorRodrigues, Paulo M. M.
dc.contributor.authorRubia, Antonio
dc.contributor.authorTaylor, A. M Robert
dc.contributor.institutionNOVA School of Business and Economics (NOVA SBE)
dc.contributor.pblJohn Wiley & Sons, Ltd.
dc.date.accessioned2024-01-30T22:24:53Z
dc.date.available2024-01-30T22:24:53Z
dc.date.issued2021-08
dc.descriptionPublisher Copyright: © 2021 The Authors. Journal of Applied Econometrics published by John Wiley & Sons Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
dc.description.abstractWe introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the Lagrange multiplier principle to a feasible generalised least squares estimate of the FIVAR model obtained under the null hypothesis. A key feature of the test we propose is that it is constructed using a heteroskedasticity-robust estimate of the variance matrix. As a result, the test has a standard χ2 limiting null distribution under considerably weaker conditions on the innovations than are permitted in the extant literature. Specifically, we allow the innovations driving the FIVAR model to follow a vector martingale difference sequence allowing for both serial and cross-sectional dependence in the conditional second-order moments. We also do not constrain the order of fractional integration of each element of the series to lie in a particular region, thereby allowing for both stationary and non-stationary dynamics, nor do we assume any particular distribution for the innovations. A Monte Carlo study demonstrates that our proposed tests avoid the large oversizing problems seen with extant tests when conditional heteroskedasticity is present in the data. We report an empirical case study for a sample of major US stocks investigating the order of fractional integration in trading volume and different measures of volatility in returns, including realised variance. Our results suggest that both return volatility and trading volume are fractionally integrated, but with the former generally found to be more persistent (having a higher fractional exponent) than the latter, when more reliable proxies for volatility such as the range or realised variance are used.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent949794
dc.identifier.doi10.1002/jae.2829
dc.identifier.issn0883-7252
dc.identifier.otherPURE: 32652429
dc.identifier.otherPURE UUID: 26d99ad3-f3e9-40b2-8fbf-a67b31772eb0
dc.identifier.otherScopus: 85109394916
dc.identifier.otherWOS: 000671738100001
dc.identifier.urihttp://hdl.handle.net/10362/162907
dc.identifier.urlhttps://www.scopus.com/pages/publications/85109394916
dc.language.isoeng
dc.peerreviewedyes
dc.relationFunding Information
dc.relationBalboa and Rubia gratefully acknowledge financial support
dc.relationfrom the Spanish Ministry of Economy
dc.relationthrough project ECO2017‐87069‐P
dc.relationRodrigues gratefully acknowledges financial support
dc.relationFCT-the Portuguese Science Foundation
dc.relationthrough project PTDC/EGE‐ECO/28924/2017
dc.relationand UID/ECO/00124/2013
dc.relationand Social Sciences DataLab
dc.relationProject 22209
dc.relationPOR Lisboa (LISBOA‐01‐0145‐FEDER‐007722
dc.relationand POR Norte (Social Sciences DataLab, Project 22209
dc.subjectSocial Sciences (miscellaneous)
dc.subjectEconomics and Econometrics
dc.titleMultivariate fractional integration tests allowing for conditional heteroskedasticity with an application to return volatility and trading volumeen
dc.typejournal article
degois.publication.firstPage544
degois.publication.issue5
degois.publication.lastPage565
degois.publication.titleJournal Of Applied Econometrics
degois.publication.volume36
dspace.entity.typePublication
rcaap.rightsopenAccess

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