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

Date
2022-09-27
Authors
Gurrib, Ikhlaas
Kamalov, Firuz
Alshareif, Elgilani E.
Journal Title
Journal ISSN
Volume Title
Publisher
Econjournals
Abstract
This 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.
Description
This work is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in International Journal of Energy Economics and Policy (2022), available online at: https://doi.org/10.32479/ijeep.13045
Keywords
COVID-19, ETF, High Frequency Trading, Machine Learning, Return, Risk, U.S. Sectors
Citation
Gurrib, 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