Marcin Wątorek, Jarosław Kwapień, Stanisław Drożdż
arXiv 2 Aug 2022 · Finance — Statistical Finance · publishedFuture Internet (2022) · 31 citations (OpenAlex)
arXiv:2208.01445 · PDF · DOI · OpenAlex · Extracted main text
Unlike price fluctuations, the temporal structure of cryptocurrency trading has seldom been a subject of systematic study. In order to fill this gap, we analyse detrended correlations of the price returns, the average number of trades in time unit, and the traded volume based on high-frequency data representing two major cryptocurrencies: bitcoin and ether. We apply the multifractal detrended cross-correlation analysis, which is considered the most reliable method for identifying nonlinear correlations in time series. We find that all the quantities considered in our study show an unambiguous multifractal structure from both the univariate (auto-correlation) and bivariate (cross-correlation) perspectives. We looked at the bitcoin--ether cross-correlations in simultaneously recorded signals, as well as in time-lagged signals, in which a time series for one of the cryptocurrencies is shifted with respect to the other. Such a shift suppresses the cross-correlations partially for short time scales, but does not remove them completely. We did not observe any qualitative asymmetry in the results for the two choices of a leading asset. The cross-correlations for the simultaneous and lagged time series became the same in magnitude for the sufficiently long scales.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Kwapień, J.; Wątorek, M.; Bezbradica, M.; Crane, M.; Mai, T.T.; Droż… (2022) 2206.07831 self | 0.874 | 6 | 2 | 100% |
| 2 | Wątorek, M.; Drożdż, S.; Kwapień, J.; Minati, L.; Oświęcimka, P.; St… (2021) self | 0.811 | 4 | 2 | 100% |
| 3 | Kwapień, J.; Oświęcimka, P.; Drożdż, S. Detrended fluctuation analys… (2015) self | 0.737 | 3 | 2 | 100% |
| 4 | Kwapień, J.; Wątorek, M.; Drożdż, J. Cryptocurrency market consolida… self | 0.737 | 3 | 2 | 100% |
| 5 | Oświęcimka, P.; Drożdż, S.; Forczek, M.; Jadach, S.; Kwapień, J. Det… | 0.737 | 3 | 2 | 100% |
| 6 | Binance, http://binance.com (accessed on 20 June (2022) | 0.644 | 2 | 2 | 100% |
| 7 | Corbet, S.; Hou, Y. G.; Hu, Y.; Larkin, C.; Oxley, L. Any port in a… (2020) | 0.644 | 2 | 2 | 100% |
| 8 | Kantelhardt, J.W.; Zschiegner, S.A.; Koscielny-Bunde, E.; Havlin, S.… (2002) | 0.644 | 2 | 2 | 100% |
| 9 | Podobnik, B.; Stanley, H.E. Detrended cross-correlation analysis: A… (2008) | 0.644 | 2 | 2 | 100% |
| 10 | Zhou, W.-X. Multifractal detrended cross-correlation analysis for tw… (2008) textit77, 066211 | 0.644 | 2 | 2 | 100% |
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