COVID-19 pandemic and cryptocurrency markets: an empirical analysis from a linear and nonlinear causal relationship
Studies in Economics and Finance
ISSN: 1086-7376
Article publication date: 26 March 2021
Issue publication date: 7 June 2021
Abstract
Purpose
This paper aims to empirically examine the effect of Coronavirus disease 2019 (COVID-19) pandemic on cryptocurrency market returns with particular attention to top five cryptocurrencies and COVID-19 confirmed and death cases.
Design/methodology/approach
The study applies the linear Toda and Yamamoto and nonlinear Diks and Panchenko Granger causality test to know the causal relationship of cryptocurrencies with COVID-19 pandemic. The study also uses the Narayan and Popp endogenous two structural break tests to capture the break period of the sample.
Findings
The findings of the study confirm the existence of unidirectional causal relation from COVID-19 confirmed and death cases to cryptocurrency price returns. While examining the break periods, the post-break period result indicates the presence of unidirectional linear causality from COVID-19 confirmed cases to Bitcoin and Ethereum price returns. This shows that prior knowledge of COVID-19 pandemic growth helps to predict the return of cryptocurrencies.
Originality/value
The study suggests the investors or crypto lovers to observe the growth of COVID-19 situations during their investment in cryptocurrency markets.
Keywords
Acknowledgements
The author gratefully acknowledge the valuable suggestions received from Prof. Syed Aun Raza Rizvi in the 14th BMEB international conference call for paper and Webinar session in the early draft of this paper. All remaining errors are belongs to author.
Citation
Sahoo, P.K. (2021), "COVID-19 pandemic and cryptocurrency markets: an empirical analysis from a linear and nonlinear causal relationship", Studies in Economics and Finance, Vol. 38 No. 2, pp. 454-468. https://doi.org/10.1108/SEF-09-2020-0385
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited