Advanced
Please use this identifier to cite or link to this item: https://digital.lib.ueh.edu.vn/handle/UEH/60668
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSalisu, A.A.-
dc.contributor.otherVo, X.V.-
dc.date.accessioned2020-12-09T05:53:52Z-
dc.date.available2020-12-09T05:53:52Z-
dc.date.issued2020-
dc.identifier.issn1057-5219-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85087760385&doi=10.1016%2fj.irfa.2020.101546&partnerID=40&md5=0b46d6547712b83b2d4aec7bf821130d-
dc.identifier.urihttp://digital.lib.ueh.edu.vn/handle/UEH/60668-
dc.description.abstractThis study derives its motivation from the current global pandemic, COVID-19, to evaluate the relevance of health-news trends in the predictability of stock returns. We demonstrate this by using data covering top-20 worst-hit countries, distinctly in terms of reported cases and deaths. The results reveal that the model that incorporates health-news index outperforms the benchmark historical average model, indicating the significance of health news searches as a good predictor of stock returns since the emergence of the pandemic. We also find that accounting for “asymmetry” effect, adjusting for macroeconomic factors and incorporating financial news improve the forecast performance of the health news-based model. These results are consistently robust to data sample (both for the in-sample and out-of-sample forecast periods), outliers and heterogeneity.en
dc.formatPortable Document Format (PDF)-
dc.language.isoeng-
dc.publisherElsevier Inc.-
dc.relation.ispartofInternational Review of Financial Analysis-
dc.relation.ispartofseriesVol. 71-
dc.rightsElsevier Inc.-
dc.subjectCOVID-19en
dc.subjectHealth newsen
dc.subjectPredictabilityen
dc.subjectStock returnsen
dc.titlePredicting stock returns in the presence of COVID-19 pandemic: The role of health newsen
dc.typeJournal Articleen
dc.identifier.doihttps://doi.org/10.1016/j.irfa.2020.101546-
ueh.JournalRankingScopus-
item.openairetypeJournal Article-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextOnly abstracts-
item.grantfulltextnone-
item.languageiso639-1en-
Appears in Collections:INTERNATIONAL PUBLICATIONS
Show simple item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.