Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/258826 
Authors: 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 15 [Issue:] 3 [Article No.:] 103 [Publisher:] MDPI [Place:] Basel [Year:] 2022 [Pages:] 1-25
Publisher: 
MDPI, Basel
Abstract: 
This paper features an analysis of cryptocurrencies and the impact of the COVID-19 pandemic on their effectiveness as a portfolio diversification tool and explores the correlations between the continuously compounded returns on Bitcoin, Ethereum and the S&P500 Index using a variety of parametric and non-parametric techniques. These methods include linear standard metrics such as the application of ordinary least squares regression (OLS) and the Pearson, Spearman and Kendall's tau measures of association. In addition, non-linear, non-parametric measures such as the Generalised Measure of Correlation (GMC) and non-parametric copula estimates are applied. The results across this range of measures are consistent. The metrics suggest that, whilst the shock of the COVID-18 pandemic does not appear to have increased the correlations between the cryptocurrency series, it appears to have increased the correlations between the returns on cryptocurrencies and those on the S&P500 Index. This suggests that investments in cryptocurrencies are not likely to offer key diversification strategies in times of crisis, on the basis of evidence provided by this crisis.
Subjects: 
Bitcoin
Ethereum
copula
kernel estimation
non-parametric
GMC
JEL: 
C19
C65
G01
G11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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