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

Natália Costa, César Silva and Paulo Ferreira
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Natália Costa: Instituto Politécnico de Portalegre, 7300-100 Portalegre, Portugal
César Silva: Instituto Politécnico de Portalegre, 7300-100 Portalegre, Portugal

IJFS, 2019, vol. 7, issue 3, 1-12

Abstract: 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.

Keywords: cryptocurrencies; detrended cross-correlation analysis; detrended fluctuation analysis; efficiency (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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