Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis.
Identifieur interne : 000574 ( Main/Exploration ); précédent : 000573; suivant : 000575Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis.
Auteurs : Tefan Cristian Gherghina [Roumanie] ; Daniel Tefan Armeanu [Roumanie] ; Camelia C T Lina Jolde [Roumanie]Source :
- International journal of environmental research and public health [ 1660-4601 ] ; 2020.
Descripteurs français
- KwdFr :
- Allemagne (MeSH), Betacoronavirus (MeSH), Chine (MeSH), Commerce (économie), Développement économique (MeSH), Espagne (MeSH), France (MeSH), Humains (MeSH), Infections à coronavirus (économie), Italie (MeSH), Pandémies (économie), Pneumopathie virale (économie), Roumanie (MeSH), Royaume-Uni (MeSH), États-Unis (MeSH).
- MESH :
- Wicri :
- geographic : République populaire de Chine, France, Allemagne, Italie, Roumanie, Espagne, Royaume-Uni, États-Unis.
English descriptors
- KwdEn :
- Betacoronavirus (MeSH), China (MeSH), Commerce (economics), Coronavirus Infections (economics), Economic Development (MeSH), France (MeSH), Germany (MeSH), Humans (MeSH), Italy (MeSH), Pandemics (economics), Pneumonia, Viral (economics), Romania (MeSH), Spain (MeSH), United Kingdom (MeSH), United States (MeSH).
- MESH :
- geographic : China, France, Germany, Italy, Romania, Spain, United Kingdom, United States.
- economics : Commerce, Coronavirus Infections, Pandemics, Pneumonia, Viral.
- Betacoronavirus, Economic Development, Humans.
Abstract
This paper examines the linkages in financial markets during coronavirus disease 2019 (COVID-19) pandemic outbreak. For this purpose, daily stock market returns were used over the period of December 31, 2019-April 20, 2020 for the following economies: USA, Spain, Italy, France, Germany, UK, China, and Romania. The study applied the autoregressive distributed lag (ARDL) model to explore whether the Romanian stock market is impacted by the crisis generated by novel coronavirus. Granger causality was employed to investigate the causalities among COVID-19 and stock market returns, as well as between pandemic measures and several commodities. The outcomes of the ARDL approach failed to find evidence towards the impact of Chinese COVID-19 records on the Romanian financial market, neither in the short-term, nor in the long-term. On the other hand, our quantitative approach reveals a negative effect of the new deaths' cases from Italy on the 10-year Romanian bond yield both in the short-run and long-run. The econometric research provide evidence that Romanian 10-year government bond is more sensitive to the news related to COVID-19 than the index of the Bucharest Stock Exchange. Granger causality analysis reveals causal associations between selected stock market returns and Philadelphia Gold/Silver Index.
DOI: 10.3390/ijerph17186729
PubMed: 32942766
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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<term>France (MeSH)</term>
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<front><div type="abstract" xml:lang="en">This paper examines the linkages in financial markets during coronavirus disease 2019 (COVID-19) pandemic outbreak. For this purpose, daily stock market returns were used over the period of December 31, 2019-April 20, 2020 for the following economies: USA, Spain, Italy, France, Germany, UK, China, and Romania. The study applied the autoregressive distributed lag (ARDL) model to explore whether the Romanian stock market is impacted by the crisis generated by novel coronavirus. Granger causality was employed to investigate the causalities among COVID-19 and stock market returns, as well as between pandemic measures and several commodities. The outcomes of the ARDL approach failed to find evidence towards the impact of Chinese COVID-19 records on the Romanian financial market, neither in the short-term, nor in the long-term. On the other hand, our quantitative approach reveals a negative effect of the new deaths' cases from Italy on the 10-year Romanian bond yield both in the short-run and long-run. The econometric research provide evidence that Romanian 10-year government bond is more sensitive to the news related to COVID-19 than the index of the Bucharest Stock Exchange. Granger causality analysis reveals causal associations between selected stock market returns and Philadelphia Gold/Silver Index.</div>
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<Abstract><AbstractText>This paper examines the linkages in financial markets during coronavirus disease 2019 (COVID-19) pandemic outbreak. For this purpose, daily stock market returns were used over the period of December 31, 2019-April 20, 2020 for the following economies: USA, Spain, Italy, France, Germany, UK, China, and Romania. The study applied the autoregressive distributed lag (ARDL) model to explore whether the Romanian stock market is impacted by the crisis generated by novel coronavirus. Granger causality was employed to investigate the causalities among COVID-19 and stock market returns, as well as between pandemic measures and several commodities. The outcomes of the ARDL approach failed to find evidence towards the impact of Chinese COVID-19 records on the Romanian financial market, neither in the short-term, nor in the long-term. On the other hand, our quantitative approach reveals a negative effect of the new deaths' cases from Italy on the 10-year Romanian bond yield both in the short-run and long-run. The econometric research provide evidence that Romanian 10-year government bond is more sensitive to the news related to COVID-19 than the index of the Bucharest Stock Exchange. Granger causality analysis reveals causal associations between selected stock market returns and Philadelphia Gold/Silver Index.</AbstractText>
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<name sortKey="Armeanu, Daniel Tefan" sort="Armeanu, Daniel Tefan" uniqKey="Armeanu D" first="Daniel Tefan" last="Armeanu">Daniel Tefan Armeanu</name>
<name sortKey="Jolde, Camelia C T Lina" sort="Jolde, Camelia C T Lina" uniqKey="Jolde C" first="Camelia C T Lina" last="Jolde">Camelia C T Lina Jolde</name>
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