The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.
Identifieur interne : 000390 ( Main/Exploration ); précédent : 000389; suivant : 000391The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.
Auteurs : Yan Li [République populaire de Chine] ; Chao Liang [République populaire de Chine] ; Feng Ma [République populaire de Chine] ; Jiqian Wang [République populaire de Chine]Source :
- Finance research letters [ 1544-6131 ] ; 2020.
Abstract
The main purpose of this paper is to investigate whether the Infectious Disease EMV tracker (IDEMV) proposed by Baker et al. (2020) has additional predictive ability for European stock market volatility during the COVID-19 pandemic. The three European stock markets we consider are France, UK and Germany. Our investigation is based on the HAR and its augmented models. We find that the IDEMV has stronger predictive power for the France and UK stock markets volatilities during the global pandemic, and the VIX has also superior predictive ability for the three European stock markets during this period.
DOI: 10.1016/j.frl.2020.101749
PubMed: 32908465
PubMed Central: PMC7467939
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.</title><author><name sortKey="Li, Yan" sort="Li, Yan" uniqKey="Li Y" first="Yan" last="Li">Yan Li</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Liang, Chao" sort="Liang, Chao" uniqKey="Liang C" first="Chao" last="Liang">Chao Liang</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Ma, Feng" sort="Ma, Feng" uniqKey="Ma F" first="Feng" last="Ma">Feng Ma</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Jiqian" sort="Wang, Jiqian" uniqKey="Wang J" first="Jiqian" last="Wang">Jiqian Wang</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32908465</idno><idno type="pmid">32908465</idno><idno type="doi">10.1016/j.frl.2020.101749</idno><idno type="pmc">PMC7467939</idno><idno type="wicri:Area/Main/Corpus">000176</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000176</idno><idno type="wicri:Area/Main/Curation">000176</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000176</idno><idno type="wicri:Area/Main/Exploration">000176</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.</title><author><name sortKey="Li, Yan" sort="Li, Yan" uniqKey="Li Y" first="Yan" last="Li">Yan Li</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Liang, Chao" sort="Liang, Chao" uniqKey="Liang C" first="Chao" last="Liang">Chao Liang</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Ma, Feng" sort="Ma, Feng" uniqKey="Ma F" first="Feng" last="Ma">Feng Ma</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Jiqian" sort="Wang, Jiqian" uniqKey="Wang J" first="Jiqian" last="Wang">Jiqian Wang</name><affiliation wicri:level="1"><nlm:affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Economics & Management, Southwest Jiaotong University, Chengdu</wicri:regionArea><wicri:noRegion>Chengdu</wicri:noRegion></affiliation></author></analytic><series><title level="j">Finance research letters</title><idno type="eISSN">1544-6131</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The main purpose of this paper is to investigate whether the Infectious Disease EMV tracker (IDEMV) proposed by Baker et al. (2020) has additional predictive ability for European stock market volatility during the COVID-19 pandemic. The three European stock markets we consider are France, UK and Germany. Our investigation is based on the HAR and its augmented models. We find that the IDEMV has stronger predictive power for the France and UK stock markets volatilities during the global pandemic, and the VIX has also superior predictive ability for the three European stock markets during this period.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32908465</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>14</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1544-6131</ISSN><JournalIssue CitedMedium="Internet"><Volume>36</Volume><PubDate><Year>2020</Year><Month>Oct</Month></PubDate></JournalIssue><Title>Finance research letters</Title><ISOAbbreviation>Financ Res Lett</ISOAbbreviation></Journal><ArticleTitle>The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.</ArticleTitle><Pagination><MedlinePgn>101749</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.frl.2020.101749</ELocationID><Abstract><AbstractText>The main purpose of this paper is to investigate whether the Infectious Disease EMV tracker (IDEMV) proposed by Baker et al. (2020) has additional predictive ability for European stock market volatility during the COVID-19 pandemic. The three European stock markets we consider are France, UK and Germany. Our investigation is based on the HAR and its augmented models. We find that the IDEMV has stronger predictive power for the France and UK stock markets volatilities during the global pandemic, and the VIX has also superior predictive ability for the three European stock markets during this period.</AbstractText><CopyrightInformation>© 2020 Elsevier Inc. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Yan</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liang</LastName><ForeName>Chao</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ma</LastName><ForeName>Feng</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Jiqian</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>School of Economics & Management, Southwest Jiaotong University, Chengdu, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>09</Month><Day>03</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Financ Res Lett</MedlineTA><NlmUniqueID>101768122</NlmUniqueID></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Global pandemic</Keyword><Keyword MajorTopicYN="N">IDEMV</Keyword><Keyword MajorTopicYN="N">VIX</Keyword><Keyword MajorTopicYN="N">Volatility forecasting</Keyword></KeywordList><CoiStatement>We declare that there is not conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>08</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>09</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>9</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>9</Month><Day>11</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>9</Month><Day>10</Day><Hour>5</Hour><Minute>35</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32908465</ArticleId><ArticleId IdType="doi">10.1016/j.frl.2020.101749</ArticleId><ArticleId IdType="pii">S1544-6123(20)30851-5</ArticleId><ArticleId IdType="pii">101749</ArticleId><ArticleId IdType="pmc">PMC7467939</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
</PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Li, Yan" sort="Li, Yan" uniqKey="Li Y" first="Yan" last="Li">Yan Li</name></noRegion><name sortKey="Liang, Chao" sort="Liang, Chao" uniqKey="Liang C" first="Chao" last="Liang">Chao Liang</name><name sortKey="Ma, Feng" sort="Ma, Feng" uniqKey="Ma F" first="Feng" last="Ma">Feng Ma</name><name sortKey="Wang, Jiqian" sort="Wang, Jiqian" uniqKey="Wang J" first="Jiqian" last="Wang">Jiqian Wang</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/CovidFranceV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000390 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000390 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= CovidFranceV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:32908465
|texte= The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:32908465" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a CovidFranceV1
| This area was generated with Dilib version V0.6.37. |  |