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Geopolitical Risk and the Risk Spillover on the US Technology Firms: A Quantile Perspective

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dc.contributor.authorWang, Deyong-
dc.contributor.authorSun, Yizhong-
dc.contributor.authorWang, Yishuo-
dc.contributor.authorGao, Nan-
dc.date.accessioned2025-07-11T06:30:09Z-
dc.date.available2025-07-11T06:30:09Z-
dc.date.issued2025-00-
dc.identifier.issn0424-267X-
dc.identifier.issn1842-3264-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/79368-
dc.description.abstractThis article employs the quantile vector autoregression (QVAR) Connectedness method to investigate the impact of geopolitical risk on major US technology firms under various market conditions. The findings reveal that: 1) the overall Connectedness index peaks at 63.76% during market uptrends and reaches a low of 38.61% at the median state; 2) Microsoft and Nvidia act as net risk transmitters, whereas Apple and the geopolitical risk index serve as net risk receivers; and 3) during the COVID-19 period in 2020, Connectedness significantly increased across all quantile levels, while a differentiated pattern emerged during the Russia-Ukraine war in 2022. The main contributions of this study include: firstly, it is the first to examine the asymmetric risk linkages between geopolitical risk and US technology firms; secondly, it enriches existing theories through both static and dynamic association analyses; and thirdly, it offers valuable risk management insights for investors. These results have important implications for portfolio management and policy formulation. © 2024 The Authors. Published by Editura ASE.-
dc.format.extent17-
dc.language영어-
dc.language.isoENG-
dc.publisherEditura Academia de studii economice-
dc.titleGeopolitical Risk and the Risk Spillover on the US Technology Firms: A Quantile Perspective-
dc.typeArticle-
dc.publisher.location루마니아-
dc.identifier.doi10.24818/18423264/59.2.25.09-
dc.identifier.scopusid2-s2.0-105009004018-
dc.identifier.wosid001530455900009-
dc.identifier.bibliographicCitationEconomic Computation and Economic Cybernetics Studies and Research, v.59, no.2, pp 142 - 158-
dc.citation.titleEconomic Computation and Economic Cybernetics Studies and Research-
dc.citation.volume59-
dc.citation.number2-
dc.citation.startPage142-
dc.citation.endPage158-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryEconomics-
dc.relation.journalWebOfScienceCategoryMathematics, Interdisciplinary Applications-
dc.subject.keywordAuthorConnectedness Analysis-
dc.subject.keywordAuthorgeopolitical risk-
dc.subject.keywordAuthorQuantile Vector Autoregression-
dc.subject.keywordAuthortechnology firms-
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학과간협동과정 > 정치경제학과 > Journal Articles

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