Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/7630
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dc.contributor.authorRiyath, M.I.M-
dc.contributor.authorAasik, A.C-
dc.date.accessioned2025-09-01T10:39:50Z-
dc.date.available2025-09-01T10:39:50Z-
dc.date.issued2025-05-10-
dc.identifier.citationInternational Journal of Accounting & Business Finance Vol.11, No.1, June 2025 Issue. pp: 221-241.en_US
dc.identifier.issn2448-9875-
dc.identifier.issn2448-9867-
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/7630-
dc.description.abstractThe technology sector’s rapid growth and increasing market concentration have fundamentally altered market dynamics and volatility patterns among leading firms. This study investigates the volatility spillovers among nine major US technology companies. Specifically, the study captures the interdependence and the level of influence corresponding to the stock return volatilities of these firms on one another. Apple, Amazon, Google, IBM, Intel, Meta, Microsoft, Nvidia, and Tesla were sourced from Investing.com. The daily data was collected between April 1, 2014, and May 31, 2024. We apply the Connectedness Approach framework to the time-varying parameter vector autoregression model. This methodology estimates several metrics: the total connectedness index, directional measures of volatility transmission, and pairwise relationship indicators. The analysis shows that Microsoft and Google emerge as dominant net transmitters, while IBM and Intel function as primary receivers. Tesla's receiver status despite large market capitalization confirms that ecosystem positioning rather than market size determines transmission hierarchy. The Total Connectedness Index shows significant variation during market crises, intensifying spillovers while preserving network structure. Amazon and Nvidia demonstrate variable transmission capacity. This study contributes to the literature by providing a comprehensive analysis of time-varying volatility transmission networks among leading technology firms, revealing systemic risk patterns and network effects crucial for investment and regulatory decision-making.en_US
dc.language.isoen_USen_US
dc.publisherFaculty of Management Studies & Commerce, University of Jaffnaen_US
dc.subjectConnectedness analysisen_US
dc.subjectNetwork analysisen_US
dc.subjectStock return volatilityen_US
dc.subjectTechnologyen_US
dc.titleDynamic volatility spillovers among major us technology companies: a time-varying connectedness analysisen_US
dc.typeArticleen_US
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