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Open AccessArticle

Long-Range Behaviour and Correlation in DFA and DCCA Analysis of Cryptocurrencies

1
Instituto Politécnico de Portalegre, 7300-100 Portalegre, Portugal
2
VALORIZA—Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal
3
CEFAGE-UE, IIFA, Universidade de Évora, Largo dos Colegiais 2, 7000 Évora, Portugal
*
Author to whom correspondence should be addressed.
Int. J. Financial Stud. 2019, 7(3), 51; https://doi.org/10.3390/ijfs7030051
Received: 25 June 2019 / Revised: 10 September 2019 / Accepted: 11 September 2019 / Published: 15 September 2019
(This article belongs to the Special Issue Econophysics Applications to Financial Markets)
In recent years, increasing attention has been devoted to cryptocurrencies, owing to their great development and valorization. In this study, we propose to analyse four of the major cryptocurrencies, based on their market capitalization and data availability: Bitcoin, Ethereum, Ripple, and Litecoin. We apply detrended fluctuation analysis (the regular one and with a sliding windows approach) and detrended cross-correlation analysis and the respective correlation coefficient. We find that Bitcoin and Ripple seem to behave as efficient financial assets, while Ethereum and Litecoin present some evidence of persistence. When correlating Bitcoin with the other cryptocurrencies under analysis, we find that for short time scales, all the cryptocurrencies have statistically significant correlations with Bitcoin, although Ripple has the highest correlations. For higher time scales, Ripple is the only cryptocurrency with significant correlation. View Full-Text
Keywords: cryptocurrencies; detrended cross-correlation analysis; detrended fluctuation analysis; efficiency cryptocurrencies; detrended cross-correlation analysis; detrended fluctuation analysis; efficiency
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MDPI and ACS Style

Costa, N.; Silva, C.; Ferreira, P. Long-Range Behaviour and Correlation in DFA and DCCA Analysis of Cryptocurrencies. Int. J. Financial Stud. 2019, 7, 51.

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