True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods

Ata Assaf (), Luis Gil-Alana and Khaled Mokni ()
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Ata Assaf: University of Balamand

Empirical Economics, 2022, vol. 63, issue 3, No 12, 1543-1570

Abstract: Abstract 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.

Keywords: Cryptocurrency markets; Multivariate long-memory tests; Spurious long memory; Cryptocurrency volatility (search for similar items in EconPapers)
JEL-codes: C12 C32 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00181-021-02165-6

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