COVID-19 news and the US equity market interactions: An inspection through econometric and machine learning lens

Rabin K. Jana (), Indranil Ghosh (), Fredj Jawadi (), Gazi Salah Uddin () and Ricardo Sousa
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Rabin K. Jana: Indian Institute of Management Raipur
Indranil Ghosh: Institute of Management Technology Hyderabad
Fredj Jawadi: Univ. Lille, ULR 4999 - LUMEN
Gazi Salah Uddin: Linköping University

Annals of Operations Research, 2025, vol. 345, issue 2, No 2, 575-596

Abstract: Abstract This study investigates the impact of COVID-19 on the US equity market during the first wave of Coronavirus using a wide range of econometric and machine learning approaches. To this end, we use both daily data related to the US equity market sectors and data about the COVID-19 news over January 1, 2020-March 20, 2020. Accordingly, we show that at an early stage of the outbreak, global COVID-19s fears have impacted the US equity market even differently across sectors. Further, we also find that, as the pandemic gradually intensified its footprint in the US, local fears manifested by daily infections emerged more powerfully compared to its global counterpart in impairing the short-term dynamics of US equity markets.

Keywords: COVID-19; The US equity market; Co-integration; Detrended cross-correlation analysis; Machine learning (search for similar items in EconPapers)
JEL-codes: C22 G1 I1 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-022-04744-x

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