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

Jana, Rabin K., Ghosh, Indranil, Jawadi, Fredj, Uddin, Gazi Salah and Sousa, Ricardo M. (2022) COVID-19 news and the US equity market interactions: an inspection through econometric and machine learning lens. Annals of Operations Research. ISSN 0254-5330

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Identification Number: 10.1007/s10479-022-04744-x

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.

Item Type: Article
Official URL: https://www.springer.com/journal/10479
Additional Information: © 2022 The Authors, under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Divisions: LSE
Subjects: H Social Sciences > HB Economic Theory
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
H Social Sciences > HV Social pathology. Social and public welfare. Criminology
JEL classification: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
G - Financial Economics > G1 - General Financial Markets > G10 - General
I - Health, Education, and Welfare > I1 - Health > I10 - General
Date Deposited: 23 Jun 2022 11:00
Last Modified: 30 Jun 2022 23:15
URI: http://eprints.lse.ac.uk/id/eprint/115427

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