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Analysis of inter-transaction time fluctuations in the cryptocurrency market.

Kwapień, Jaroslaw ORCID: 0000-0001-8813-9637, Wątorek, Marcin ORCID: 0000-0002-2131-7440, Bezbradica, Marija ORCID: 0000-0001-9366-5113, Crane, Martin ORCID: 0000-0001-7598-3126, Mai, Tai Tan ORCID: 0000-0001-6657-0872 and Drozdz, Stanislaw ORCID: 0000-0003-1613-6175 (2022) Analysis of inter-transaction time fluctuations in the cryptocurrency market. Chaos, 32 (8). ISSN 10541500

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Abstract

We analyse tick-by-tick data representing major cryptocurrencies traded on some different cryptocurrency trading platforms. We focus on such quantities like the inter-transaction times, the number of transactions in time unit, the traded volume, and volatility. We show that the inter-transaction times show long-range power-law autocorrelations. These lead to multifractality expressed by the right-side asymmetry of the singularity spectra f(α) indicating that the periods of increased market activity are characterised by richer multifractality compared to the periods of quiet market. We also show that neither the stretched exponential distribution nor the power-law-tail distribution are able to model universally the cumulative distribution functions of the quantities considered in this work. For each quantity, some data sets can be modeled by the former, some data sets by the latter, while both fail in other cases. An interesting, yet difficult to account for, observation is that parallel data sets from different trading platforms can show disparate statistical properties.

Item Type:Article (Published)
Refereed:Yes
Additional Information:Article number: 083142
Uncontrolled Keywords:Complex Systems; Cryptocurrencies; Inter-Transaction Times
Subjects:Business > Finance
Physical Sciences > Statistical physics
Mathematics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Publisher:AIP
Official URL:https://doi.org/10.1063/5.0104707
Copyright Information:© 2022 Authors
Funders:Science Foundation Ireland under Grant Agreement No. 13/RC/2106_P2 at the ADAPT SFI Research Centre at DCU
ID Code:27775
Deposited On:26 Sep 2022 09:29 by Martin Crane . Last Modified 26 Sep 2022 09:29

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