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dc.contributor.authorCaporale, GM-
dc.contributor.authorGil-Alana, L-
dc.contributor.authorPlastun, A-
dc.identifier.citationCaporale, G.M., Gil-Alana, L. and Plastun, A. (2019) 'Long memory and data frequency in financial markets', Journal of Statistical Computation and Simulation, 89 (10), pp. 1763 - 1779. doi: 10.1080/00949655.2019.1599377.en_US
dc.description.abstract© 2019 The Author(s). This paper investigates persistence in financial time series at three different frequencies (daily, weekly and monthly). The analysis is carried out for various financial markets (stock markets, FOREX, commodity markets) over the period from 2000 to 2016 using two different long memory approaches (R/S analysis and fractional integration) for robustness purposes. The results indicate that persistence is higher at lower frequencies, for both returns and their volatility. This is true of the stock markets (both developed and emerging) and partially of the FOREX and commodity markets examined. Such evidence against the random walk behaviour implies predictability and is inconsistent with the Efficient Market Hypothesis (EMH), since abnormal profits can be made using trading strategies based on trend analysis.-
dc.description.sponsorshipMinisterio de Ciencia y Tecnología and the Ministry of Education and Science of Ukraineen_US
dc.description.sponsorshipMinisterio de Ciencia y Tecnología [grant number ECO2017-85503-R]; Ministry of Education and Science of Ukraine [grant number 0117U003936].-
dc.format.extent1763 - 1779-
dc.publisherTaylor & Francisen_US
dc.rights© 2019 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.-
dc.subjectlong memoryen_US
dc.subjectR/S analysisen_US
dc.subjectfractional integrationen_US
dc.titleLong memory and data frequency in financial marketsen_US
dc.relation.isPartOfJournal of Statistical Computation and Simulation-
Appears in Collections:Dept of Economics and Finance Research Papers

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