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Título: Extreme spillovers between insurance tokens and insurance stocks: evidence from the quantile connectedness approach
Fecha de publicación: sep-2023
Editorial: Elsevier
Cita bibliográfica: Journal of Behavioral and Experimental Finance, 2023, Vol. 39 : 100823
ISSN: Print: 2214-6350
Electronic: 2214-6369
Palabras clave: Insurance tokens
Insurance stocks
Connectedness
COVID-19 pandemic crisis
Resumen: This study examines potential tail spillovers between insurance tokens and conventional stocks using the quantile connectedness approach by Ando et al. (2022). In particular, this study explores static and dynamic spillovers at lower and upper tails of the return distribution. In line with previous studies, tokens and conventional stocks within the insurance market may show positive but low connectedness levels. Furthermore, our findings confirm a higher sensitivity of the insurance system at both tails of the distribution in comparison with the median (𝑄 = 0.50). As expected, dynamic connectedness measures change over time, intensifying at the extremes of the distribution. This finding is confirmed by the robustness test that consists of analyzing the RTD (Relative Tail Dependence) measure, as we reject the symmetric response, since its values are clearly different from zero in most of the sample period. These results are of interest to portfolio managers, as the findings will allow them to suggest adjustments to investment portfolios according to the evolution of the dynamic spillovers found.
Autor/es principal/es: Yousaf, Imran
Jareño, Francisco
Martínez Serna, María Isabel
Facultad/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Organización de Empresas y Finanzas
Versión del editor: https://www.sciencedirect.com/science/article/pii/S2214635023000370?via%3Dihub
URI: http://hdl.handle.net/10201/151241
DOI: https://doi.org/10.1016/j.jbef.2023.100823
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 16
Derechos: info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Descripción: © 2023 The Author(s). This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is Published Manuscript version of a Published Work that appeared in final form in Journal of Behavioral and Experimental Finance. To access the final edited and published work see https://doi.org/10.1016/j.jbef.2023.100823
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