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Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis

In our study, we employ DCC-GARCH and Wavelet coherence analysis to examine the co-movement between global covid-19 indicators (cases, recoveries and deaths) and stock returns of main equity markets in G20 countries using daily data spanning between February 2, 2020 and August 28, 2021. Our empirica...

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Detalles Bibliográficos
Autores principales: Phiri, Andrew, Anyikwa, Izunna, Moyo, Clement
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988315/
https://www.ncbi.nlm.nih.gov/pubmed/36911877
http://dx.doi.org/10.1016/j.heliyon.2023.e14195
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author Phiri, Andrew
Anyikwa, Izunna
Moyo, Clement
author_facet Phiri, Andrew
Anyikwa, Izunna
Moyo, Clement
author_sort Phiri, Andrew
collection PubMed
description In our study, we employ DCC-GARCH and Wavelet coherence analysis to examine the co-movement between global covid-19 indicators (cases, recoveries and deaths) and stock returns of main equity markets in G20 countries using daily data spanning between February 2, 2020 and August 28, 2021. Our empirical results show that the co-movement between COVID-19 and G20 stock returns has been switching between negative and positive correlations across the entire time window. The wavelet coherence analysis further reveal that negative (positive) co-movements predominantly exist as lower (higher frequencies) for cases and deaths and are more mixed for recoveries. The findings also show that the short-frequency components correspond to periods around the initial announcement of the initial pandemic and also around the announced of subsequent variants of the COVID-19 virus. Policy and market implications from our study are also discussed.
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spelling pubmed-99883152023-03-07 Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis Phiri, Andrew Anyikwa, Izunna Moyo, Clement Heliyon Research Article In our study, we employ DCC-GARCH and Wavelet coherence analysis to examine the co-movement between global covid-19 indicators (cases, recoveries and deaths) and stock returns of main equity markets in G20 countries using daily data spanning between February 2, 2020 and August 28, 2021. Our empirical results show that the co-movement between COVID-19 and G20 stock returns has been switching between negative and positive correlations across the entire time window. The wavelet coherence analysis further reveal that negative (positive) co-movements predominantly exist as lower (higher frequencies) for cases and deaths and are more mixed for recoveries. The findings also show that the short-frequency components correspond to periods around the initial announcement of the initial pandemic and also around the announced of subsequent variants of the COVID-19 virus. Policy and market implications from our study are also discussed. Elsevier 2023-03-07 /pmc/articles/PMC9988315/ /pubmed/36911877 http://dx.doi.org/10.1016/j.heliyon.2023.e14195 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Phiri, Andrew
Anyikwa, Izunna
Moyo, Clement
Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title_full Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title_fullStr Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title_full_unstemmed Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title_short Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis
title_sort co-movement between covid-19 and g20 stock market returns: a time and frequency analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988315/
https://www.ncbi.nlm.nih.gov/pubmed/36911877
http://dx.doi.org/10.1016/j.heliyon.2023.e14195
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