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The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis

Open access
Goodell, John W., Goutte, Stephane·2021·Finance Research Letters

Abstract

We apply wavelet methods to daily data of COVID-19 world deaths and daily Bitcoin prices from 31th December 2019 to 29th April 2020. We find, especially for the period post April 5, that levels of COVID-19 caused a rise in Bitcoin prices. We contribute to the fast-growing body of work on the financial impacts of COVID-19, as well as to ongoing consideration of whether Bitcoin is a safe haven investment. Our results should be of great interest to both scholars and policy makers, as well as investment professionals interested in the financial implications of both COVID-19 and cryptocurrencies.

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Metadata

Authors
Goodell, J. W., & Goutte, S.
Venue
Finance Research Letters
Publisher
Elsevier BV
Published
2021-01
Volume
38
Pages
101625
ISSN
1544-6123 (ISSN-L)
OpenAlex
W3025889651
Cited by
474
References
29
FWCI
71.90
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. https://app.cochat.ai/papers/10.1016/j.frl.2020.101625
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Goodell, J. W., & Goutte, S. (2021). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters. https://doi.org/10.1016/j.frl.2020.101625

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.