Katsiampa, P. orcid.org/0000-0003-0477-6503 (2019) An empirical investigation of volatility dynamics in the cryptocurrency market. Research in International Business and Finance, 50. pp. 322-335. ISSN 0275-5319
Abstract
By employing an asymmetric Diagonal BEKK model, this paper examines volatility dynamics of five major cryptocurrencies, namely Bitcoin, Ether, Ripple, Litecoin, and Stellar Lumen. It is shown that the conditional variances of all the five cryptocurrencies are significantly affected by both previous squared errors and past conditional volatility. Moreover, in the case of Bitcoin, Ether, Ripple, and Litecoin, asymmetric past shocks have a significant effect in the current conditional variance. Similar results are obtained for the cryptocurrencies' conditional covariances, which are significantly affected by cross products of previous error terms and past covariance terms while capturing asymmetric effects of past shocks accordingly. It is also shown that time-varying conditional correlations exist and are mostly positive. Finally, the cryptocurrencies' volatility dynamics are found to be responsive to major news, with Bitcoin and Litecoin exhibiting one structural breakpoint each in the conditional variance. The results improve our understanding of interdependencies between cryptocurrencies as well as of the events that affect their volatility dynamics and thus have important implications for both cryptocurrency users and investors.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Elsevier. This is an author produced version of a paper subsequently published in Research in International Business and Finance. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Bitcoin; Cryptocurrency; Asymmetric Diagonal BEKK; MGARCH; Volatility; Conditional correlations |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jun 2019 15:30 |
Last Modified: | 07 Dec 2021 10:50 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ribaf.2019.06.004 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147457 |