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Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model

Τhis paper presents new evidence on connectedness across cryptocurrencies in the era of the Covid-19 pandemic. The results from the TVP-VAR dynamic connectedness approach show that the degree of connectedness is time-varying, indicating a decline during the Covid-19 period. Next, this paper highligh...

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Detalles Bibliográficos
Autor principal: Giannellis, Nikolaos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630299/
https://www.ncbi.nlm.nih.gov/pubmed/36345470
http://dx.doi.org/10.1016/j.ribaf.2022.101801
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author Giannellis, Nikolaos
author_facet Giannellis, Nikolaos
author_sort Giannellis, Nikolaos
collection PubMed
description Τhis paper presents new evidence on connectedness across cryptocurrencies in the era of the Covid-19 pandemic. The results from the TVP-VAR dynamic connectedness approach show that the degree of connectedness is time-varying, indicating a decline during the Covid-19 period. Next, this paper highlights the nonlinear characteristics of the relationship between connectedness and its explanatory variables. The results from the LSTR model indicate that the regression coefficients change smoothly between the low and the upper regimes as anxiety across Twitter users increases. As the latter changes smoothly from low to high values, the impact of higher Disease-based volatility or Twitter-based uncertainty on connectedness turns gradually from positive to negative. The upper regime is dominant during the Covid-19 pandemic. Important implications for investors and policy makers are derived.
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spelling pubmed-96302992022-11-03 Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model Giannellis, Nikolaos Res Int Bus Finance Article Τhis paper presents new evidence on connectedness across cryptocurrencies in the era of the Covid-19 pandemic. The results from the TVP-VAR dynamic connectedness approach show that the degree of connectedness is time-varying, indicating a decline during the Covid-19 period. Next, this paper highlights the nonlinear characteristics of the relationship between connectedness and its explanatory variables. The results from the LSTR model indicate that the regression coefficients change smoothly between the low and the upper regimes as anxiety across Twitter users increases. As the latter changes smoothly from low to high values, the impact of higher Disease-based volatility or Twitter-based uncertainty on connectedness turns gradually from positive to negative. The upper regime is dominant during the Covid-19 pandemic. Important implications for investors and policy makers are derived. Elsevier B.V. 2022-12 2022-11-03 /pmc/articles/PMC9630299/ /pubmed/36345470 http://dx.doi.org/10.1016/j.ribaf.2022.101801 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Giannellis, Nikolaos
Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title_full Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title_fullStr Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title_full_unstemmed Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title_short Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model
title_sort cryptocurrency market connectedness in covid-19 days and the role of twitter: evidence from a smooth transition regression model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630299/
https://www.ncbi.nlm.nih.gov/pubmed/36345470
http://dx.doi.org/10.1016/j.ribaf.2022.101801
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