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Please use this identifier to cite or link to this item: https://digital.lib.ueh.edu.vn/handle/UEH/68836
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dc.contributor.authorRabeh Khalfaoui-
dc.contributor.otherShawkat Hammoudeh-
dc.contributor.otherMohd Ziaur Rehman-
dc.date.accessioned2023-05-30T02:27:49Z-
dc.date.available2023-05-30T02:27:49Z-
dc.date.issued2023-
dc.identifier.issn1566-0141 (Print), 1873-6173 (Online)-
dc.identifier.urihttps://digital.lib.ueh.edu.vn/handle/UEH/68836-
dc.description.abstractIn this study we advance the understanding of the spillovers and connectedness network among conventional and Islamic BRICS stock markets, cryptos (Bitcoin, Ethereum, Litecoin) and various global uncertainties, using a quantile vector autoregression method and daily data covering the period October 8, 2016, to May 28, 2021. Further, the study uses a network and sensitivity analyses to assess the nexus, examines risk causes, and the transfer paths in these markets under bearish, normal, and bullish markets. The evidence offers major findings. First, the overall static and dynamic connectedness is very high and more intense at extreme events. Second, the network connectedness structure shows that the markets have played both roles: net transmitters and receivers of shocks under several market states. Finally, the sensitivity to quantiles analysis shows switching behavior of net transfer spillovers over the quantiles. This could be beneficial to investors aiming at optimizing hedging strategies. Policymakers should consider carefully the overall network connectedness in the market system and formulate appropriate policies to conceive stock market price sensitivity.en
dc.formatPortable Document Format (PDF)-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofEmerging Markets Review-
dc.relation.ispartofseriesVol. 54-
dc.rightsElseviervi
dc.subjectSpillover-
dc.subjectCryptos-
dc.subjectUncertainty-
dc.subjectNetwork analysis-
dc.subjectSensitivity-
dc.subjectBRICS-
dc.titleSpillovers and connectedness among BRICS stock markets, cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network-
dc.typeJournal Article-
dc.identifier.doihttps://doi.org/10.1016/j.ememar.2023.101002-
ueh.JournalRankingScopus-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeJournal Article-
item.fulltextOnly abstracts-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Collections:INTERNATIONAL PUBLICATIONS
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