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

Ikhlaas Gurrib, Firuz Kamalov and Elgilani E. Alshareif
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Ikhlaas Gurrib: Faculty of Management, School of Graduate Studies, Canadian University Dubai, UAE,
Firuz Kamalov: Faculty of Engineering and Architecture, Canadian University Dubai, UAE,
Elgilani E. Alshareif: Faculty of Management, School of Graduate Studies, Canadian University Dubai, UAE.

International Journal of Energy Economics and Policy, 2022, vol. 12, issue 5, 441-456

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-minute 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-minute Standard & 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 minutes. Average returns in the first 15 minutes 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 minutes 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.

Keywords: U.S. Sectors; COVID-19; High Frequency Trading; Risk; Return; ETF; Machine Learning (search for similar items in EconPapers)
JEL-codes: G11 G12 G14 G15 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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