Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/112647
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dc.contributor.authorAndrada Félix, Juliánen_US
dc.contributor.authorFernandez-Perez, Aen_US
dc.contributor.authorFernández Rodríguez, Fernandoen_US
dc.contributor.authorSosvilla Rivero,Simón Javieren_US
dc.date.accessioned2021-11-15T08:46:48Z-
dc.date.available2021-11-15T08:46:48Z-
dc.date.issued2022en_US
dc.identifier.issn0377-7332en_US
dc.identifier.urihttp://hdl.handle.net/10553/112647-
dc.description.abstractThis paper examines the interconnection between four implied volatility indices representative of the investors' consensus view of expected stock market volatility at different maturities during the period from 3 January 2011 to 4 May 2018. To this end, we first perform static analysis to measure the total volatility connectedness in the entire period using a framework proposed by Diebold and Yilmaz (J Econ 182: 119–134, 2014). Second, we apply a dynamic analysis to evaluate both the net directional connectedness for each market using the TVP-VAR connectedness approach developed by Antonakakis and Gabauer (Refined measures of dynamic connectedness based on TVP-VAR. MPRA, Working Paper No. 78282, 2017). Our results suggest that 72.27% of the total variance of the forecast errors is explained by shocks across the examined maturities, indicating that the remainder 27.73% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability. Our results are robust to control by macroeconomic and uncertainty factors, and persistent across US and European implied volatility indices.en_US
dc.languageengen_US
dc.relationPID2019-105986 GB-C21en_US
dc.relation.ispartofEmpirical Economicsen_US
dc.sourceEmpirical Economics [ISSN 0377-7332], n. 62, p. 905–931en_US
dc.subject531206 Finanzas y segurosen_US
dc.subject530904 Estructura del mercadoen_US
dc.subject.otherImplied volatility indicesen_US
dc.subject.otherFinancial market linkagesen_US
dc.subject.otherConnectednessen_US
dc.subject.otherVector autoregressionen_US
dc.subject.otherVariance decompositionen_US
dc.titleTime connectedness of fearen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.typearticleen_US
dc.identifier.doi10.1007/s00181-021-02056-wen_US
dc.identifier.isiWOS:000644384200001-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-ECOen_US
dc.description.sjr0,664
dc.description.jcr3,2
dc.description.sjrqQ1
dc.description.jcrqQ2
dc.description.ssciSSCI
dc.description.miaricds11,0
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.orcid0000-0001-8598-3234-
crisitem.author.orcid0000-0002-8808-9286-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.fullNameAndrada Félix, Julián-
crisitem.author.fullNameFernández Rodríguez,Fernando Emilio-
crisitem.author.fullNameSosvilla Rivero,Simón Javier-
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