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COVID-19 and stock market volatility: An industry level analysis

COVID-19 has had significant impact on US stock market volatility. This study focuses on understanding the regime change from lower to higher volatility identified with a Markov Switching AR model. Utilizing machine learning feature selection methods, economic indicators are chosen to best explain c...

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Detalles Bibliográficos
Autores principales: Baek, Seungho, Mohanty, Sunil K., Glambosky, Mina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467874/
https://www.ncbi.nlm.nih.gov/pubmed/32895607
http://dx.doi.org/10.1016/j.frl.2020.101748
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author Baek, Seungho
Mohanty, Sunil K.
Glambosky, Mina
author_facet Baek, Seungho
Mohanty, Sunil K.
Glambosky, Mina
author_sort Baek, Seungho
collection PubMed
description COVID-19 has had significant impact on US stock market volatility. This study focuses on understanding the regime change from lower to higher volatility identified with a Markov Switching AR model. Utilizing machine learning feature selection methods, economic indicators are chosen to best explain changes in volatility. Results show that volatility is affected by specific economic indicators and is sensitive to COVID-19 news. Both negative and positive COVID-19 information is significant, though negative news is more impactful, suggesting a negativity bias. Significant increases in total and idiosyncratic risk are observed across all industries, while changes in systematic risk vary across industry.
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spelling pubmed-74678742020-09-03 COVID-19 and stock market volatility: An industry level analysis Baek, Seungho Mohanty, Sunil K. Glambosky, Mina Financ Res Lett Article COVID-19 has had significant impact on US stock market volatility. This study focuses on understanding the regime change from lower to higher volatility identified with a Markov Switching AR model. Utilizing machine learning feature selection methods, economic indicators are chosen to best explain changes in volatility. Results show that volatility is affected by specific economic indicators and is sensitive to COVID-19 news. Both negative and positive COVID-19 information is significant, though negative news is more impactful, suggesting a negativity bias. Significant increases in total and idiosyncratic risk are observed across all industries, while changes in systematic risk vary across industry. Elsevier Inc. 2020-11 2020-09-03 /pmc/articles/PMC7467874/ /pubmed/32895607 http://dx.doi.org/10.1016/j.frl.2020.101748 Text en © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Baek, Seungho
Mohanty, Sunil K.
Glambosky, Mina
COVID-19 and stock market volatility: An industry level analysis
title COVID-19 and stock market volatility: An industry level analysis
title_full COVID-19 and stock market volatility: An industry level analysis
title_fullStr COVID-19 and stock market volatility: An industry level analysis
title_full_unstemmed COVID-19 and stock market volatility: An industry level analysis
title_short COVID-19 and stock market volatility: An industry level analysis
title_sort covid-19 and stock market volatility: an industry level analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467874/
https://www.ncbi.nlm.nih.gov/pubmed/32895607
http://dx.doi.org/10.1016/j.frl.2020.101748
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