How connected is the oil-bank network? Firm-level and high-frequency evidence

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dc.contributor.author Zhang, Yunhan
dc.contributor.author Gabauer, David
dc.contributor.author Gupta, Rangan
dc.contributor.author Ji, Qiang
dc.date.accessioned 2024-06-27T04:56:53Z
dc.date.available 2024-06-27T04:56:53Z
dc.date.issued 2024-08
dc.description.abstract By introducing a new generalized forecast error variance decomposition (GFEVD) approach that splits the same into its contemporaneous and lagged components, we investigate the risk spillover effects of different order moments, derived from intraday data, for the top 10 banks and top 10 oil and gas companies in the U.S., covering the period from December 29, 2017 to December 30, 2022. The study finds that, first, the dynamic total connectedness of all order moments is heterogeneous over time driven by economic events. Second, except realized volatility spillovers, the vast majority of overall spillovers are attributable to contemporaneous spillovers, while only a tiny fraction is associated with lagged spillovers. Finally, realized skewness (crash risk) and realized kurtosis (extreme events) in banks and oil and gas companies originate mainly from intra-industry rather than inter-industry transmission. en_US
dc.description.department Economics en_US
dc.description.librarian hj2024 en_US
dc.description.sdg SDG-08:Decent work and economic growth en_US
dc.description.sponsorship The National Natural Science Foundation of China. en_US
dc.description.uri https://www.elsevier.com/locate/eneeco en_US
dc.identifier.citation Zhang, Y., Gabauer, D., Gupta, R. & Ji, Q. 2024, 'How connected is the oil-bank network? Firm-level and high-frequency evidence', Energy Economics, vol. 136, art. 107684, pp. 1-16, doi : 10.1016/j.eneco.2024.107684. en_US
dc.identifier.issn 0140-9883 (print)
dc.identifier.issn 1873-6181 (online)
dc.identifier.other 10.1016/j.eneco.2024.107684
dc.identifier.uri http://hdl.handle.net/2263/96683
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.rights © 2024 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Energy Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Energy Economics, vol. 136, art. 107684, pp. 1-16, 2024, doi : 10.1016/j.eneco.2024.107684. en_US
dc.subject Generalized forecast error variance decomposition (GFEVD) en_US
dc.subject GFEVD decomposition en_US
dc.subject Dynamic connectedness en_US
dc.subject Higher moments en_US
dc.subject Banking connectedness en_US
dc.subject Time-varying parameter vector autoregressive (TVP-VAR) en_US
dc.subject SDG-08: Decent work and economic growth en_US
dc.title How connected is the oil-bank network? Firm-level and high-frequency evidence en_US
dc.type Preprint Article en_US


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