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Title: True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods
Authors: Assaf, Ata 
Gil-Alana, Luis Alberiko
Mokni, Khaled
Affiliations: Department of Business Administration 
Keywords: Cryptocurrency markets
Cryptocurrency volatility
Multivariate long-memory tests
Spurious long memory
Issue Date: 2022
Part of: Empirical economics
Volume: 63
Issue: 3
Start page: 1543
End page: 1570
This paper applies a new proposed multivariate score-type test against spurious long memory to a group of cryptocurrency market returns. The test statistic developed by Sibbertsen et al. (J Econ 203(1): 33–49, 2018) is based on the multivariate local Whittle likelihood function and is proven to be consistent against the alternative two cases of random level shifts and smooth trends. We apply the test to the returns, absolute returns, and modified absolute returns. Overall, the recently developed test statistic fails to reject the null hypothesis of true long memory for most cryptocurrencies, except for the Stellar market. Therefore, applying the new test statistic supports the argument that the long memory in the cryptocurrency markets is real and is not a spurious one. Our results are further supported by applying other consistent local Whittle methods that allow for the estimation of the memory parameter by accounting for the presence of perturbations or low-frequency contaminations.
ISSN: 03777332
DOI: 10.1007/s00181-021-02165-6
Ezproxy URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Business Administration

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