High Frequency Return and Risk Patterns in U.S. Sector ETFs during COVID-19

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dc.contributor.authorGurrib, Ikhlaas
dc.contributor.authorKamalov, Firuz
dc.contributor.authorAlshareif, Elgilani E.
dc.date.accessioned2022-10-20T15:31:53Z
dc.date.available2022-10-20T15:31:53Z
dc.date.copyright© 2022
dc.date.issued2022-09-27
dc.description.abstractThis study investigates intraday patterns in the eleven sectors of the United States (U.S.). Key contributions are (i) risk and return patterns at specific trading periods on the New York Stock Exchange (NYSE), (ii) whether a specific day return model can predict the next 15-min positive return, and (iii) the impact of the first vaccination rollout in the U.S. on intraday Exchange-Traded-Funds (ETF) returns. Time-dependent regressions capture risk and return relationships, decision trees in machine learning compare return models, and impulse responses capture the effect of the 2019 coronavirus (COVID-19) vaccine rollout in U.S. 15-min Standard and Poor’s Depository Receipts (SPDR) Select Sector ETF data is used over 12th March 2020-23rd February 2021. Findings support sector ETF returns fluctuate the most in the first and last 15 min. Average returns in the first 15 min are the highest, converging to near zero as the trading session continues. Overnight returns contribute the most to volatility. U-shaped patterns into both return and risk exist, especially on Mondays. Mondays and Fridays have the most significant positive returns 15 min after the open. Prediction scores using an all-return model were superior to any specific day return model. The first vaccination rollout has a positive effect only in energy, technology, and financial sector ETFs, however with a short-lasting effect on ETFs returns. © 2022, Econjournals. All rights reserved.
dc.identifier.citationGurrib, I., Kamalov, F., & Alshareif, E. E. (2022). High frequency return and risk patterns in U.S. sector ETFs during COVID-19. International Journal of Energy Economics and Policy, 12(5), 441-456. https://doi.org/10.32479/ijeep.13045
dc.identifier.issn21464553
dc.identifier.urihttps://doi.org/10.32479/ijeep.13045
dc.identifier.urihttp://hdl.handle.net/20.500.12519/714
dc.language.isoen_US
dc.publisherEconjournals
dc.relationAuthors Affiliations : Gurrib, I., Faculty of Management, School of Graduate Studies, Canadian University, Dubai, United Arab Emirates; Kamalov, F., Faculty of Engineering and Architecture, Canadian University, Dubai, United Arab Emirates; Alshareif, E.E., Faculty of Management, School of Graduate Studies, Canadian University, Dubai, United Arab Emirates
dc.relation.ispartofseriesInternational Journal of Energy Economics and Policy; Volume 12, Issue 5
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License
dc.rights.holderCopyright : © 2022, Econjournals. All rights reserved.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCOVID-19
dc.subjectETF
dc.subjectHigh Frequency Trading
dc.subjectMachine Learning
dc.subjectReturn
dc.subjectRisk
dc.subjectU.S. Sectors
dc.titleHigh Frequency Return and Risk Patterns in U.S. Sector ETFs during COVID-19
dc.typeArticle

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