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dc.rights.licenseKūrybinių bendrijų licencija / Creative Commons licenceen_US
dc.contributor.authorPanazan, Oana
dc.contributor.authorGheorghe, Catalin
dc.date.accessioned2024-04-18T05:47:19Z
dc.date.available2024-04-18T05:47:19Z
dc.date.issued2023
dc.date.submitted2023-01-27
dc.identifier.isbn9786094763335en_US
dc.identifier.issn2029-4441en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/154011
dc.description.abstractThe spread of the COVID-19 virus on all continents has caused a rapid evolution of the volatility of stock indices. To prevent and counteract the effects of this global event, researchers have tried to identify the causes, amplitude, and persistence of volatility. To measure volatility using statistical models, most authors chose the number of illnesses or deaths caused by the COVID-19 virus. However, the method of recording and reporting the number of illnesses and deaths by each state, assumed certain shortcomings reported in the literature. As an alternative, Hale et al. (2021, p. 8) proposed the Government Response Stringency Index (SI). The research proposes the determination of volatility with GARCH and VAR methods using the SI index as a variable. For this purpose, 28 countries from all continents were considered. The analysis period was March 19, 2020 to December 31, 2021. The main findings are: 1) the determination of volatility for 28 analysed countries; 2) some countries show better adaptability to the pandemic; 3) the differences between the volatility calculated with the SI index and the number of illnesses or deaths are small; 4) the links between the markets are stronger in the postcrisis period. Based on these results, comparative analyzes can be carried out between states, geographical areas and continents. Furthermore, the results allow us to appreciate other major events that affected the world capital market.en_US
dc.format.extent13 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.isreferencedbyScopusen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/153869en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.source.urihttps://bm.vgtu.lt/index.php/verslas/2023/schedConf/presentationsen_US
dc.subjectGRSIen_US
dc.subjectvolatilityen_US
dc.subjectCOVID-19 pandemicen_US
dc.subjectindexen_US
dc.subjectcasualtiesen_US
dc.subjectnumber of casualtiesen_US
dc.titleGovernment response stringency index: an alternative for the volatility determining during pandemicsen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeFinance and investment: new challenges and opportunitiesen_US
dcterms.dateAccepted2023-04-05
dcterms.issued2023
dcterms.licenseCC BYen_US
dcterms.references45en_US
dc.description.versionTaip / Yesen_US
dc.type.pubtypeP1d - Straipsnis recenzuotame konferencijos darbų leidinyje / Paper published in peer-reviewed conference publicationen_US
dc.contributor.orcidhttps://orcid.org/0000-0002-1897-575X, Panazan Oana
dc.contributor.orcidhttps://orcid.org/0000-0003-4090-1439, Gheorghe Catalin
dc.contributor.institutionTransylvania University of Brasoven_US
dcterms.sourcetitle13th International Scientific Conference “Business and Management 2023”en_US
dc.description.volumeIen_US
dc.identifier.eisbn9786094763342en_US
dc.identifier.eissn2029-929Xen_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.date.firstonline2023-06-07
dc.identifier.doihttps://doi.org/10.3846/bm.2023.972en_US


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Kūrybinių bendrijų licencija / Creative Commons licence
Except where otherwise noted, this item's license is described as Kūrybinių bendrijų licencija / Creative Commons licence