Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27987
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dc.contributor.authorCaporale, GM-
dc.contributor.authorPlastun, A-
dc.date.accessioned2024-01-09T10:43:46Z-
dc.date.available2024-01-09T10:43:46Z-
dc.date.issued2024-01-15-
dc.identifierORCID iD: Guglielmo Maria Caporale https://orcid.org/0000-0002-0144-4135-
dc.identifierORCID iD: Alex Plastun https://orcid.org/0000-0001-8208-7135-
dc.identifier2302639-
dc.identifier.citationCaporale, G.M. and Plastun, A. (2024) 'Persistence in high frequency financial data: the case of the Eurostoxx 50 futures prices', Cogent Economics and Finance, 12 (1), 2302639, pp. 1 - 9. doi: 10.1080/23322039.2024.2302639.en_US
dc.identifier.issn2332-2039-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/27987-
dc.descriptionJEL Classification: C22, G12en_US
dc.descriptionAn earlier version of this paper is available as a working paper at: https://www.brunel.ac.uk/economics-and-finance/research/pdf/2215-Oct-GMC-High-Frequency-persistence.pdf . It has not been certified by peer review.-
dc.description.abstractCopyright © 2024 The Author(s). Differences in the behaviour of asset prices depending on data frequency have not been thoroughly investigated in the literature despite their possible importance. In particular, high-frequency data might contain more information about financial assets because they are updated more rapidly in response to news. This paper explores persistence in high-frequency data (and also daily and monthly ones) in the case of the EuroStoxx 50 futures prices over the period from 2002 to 2018 (720 million trade records) using R/S analysis and the Hurst exponent as a measure of persistence. The results show that persistence is sensitive to the data frequency. More specifically, monthly data are highly persistent, daily ones follow a random walk, and intraday ones are anti-persistent. In addition, persistence varies over time. These findings imply that the Efficient Market Hypothesis (EMH) only holds in the case of daily data, whilst it is possible to make abnormal profits using trading strategies based on reversal strategies at the intraday frequency.en_US
dc.description.sponsorshipAlex Plastun also gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0121U100473).-
dc.format.extent1 - 16-
dc.format.mediumElectronic-
dc.language.isoen_USen_US
dc.publisherTaylor & Francisen_US
dc.relation.urihttps://www.brunel.ac.uk/economics-and-finance/research/pdf/2215-Oct-GMC-High-Frequency-persistence.pdf-
dc.relation.urihttps://www.cesifo.org/DocDL/cesifo1_wp10045.pdf-
dc.relation.urihttps://www.econstor.eu/handle/10419/267278-
dc.relation.urihttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4266610-
dc.rightsCopyright © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectpersistenceen_US
dc.subjectlong memoryen_US
dc.subjectR/S analysisen_US
dc.subjecthigh-frequency dataen_US
dc.subjectstock market-
dc.subjectmarket efficiency-
dc.titlePersistence in high frequency financial data: the case of the Eurostoxx 50 futures pricesen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/23322039.2024.2302639-
dc.relation.isPartOfCogent Economics and Finance-
pubs.issue1-
pubs.publication-statusPublished-
pubs.volume12-
dc.rights.holderThe Author(s)-
Appears in Collections:Dept of Economics and Finance Research Papers

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