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One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles

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  • Aurelio F. Bariviera

Abstract

This paper studies of the multifractal dynamics in 84 cryptocurrencies. It fills an important gap in the literature, by studying this market using two alternative multi-scaling methodologies. We find compelling evidence that cryptocurrencies have different degree of long range dependence, and --more importantly -- follow different stochastic processes. Some of them follow models closer to monofractal fractional Gaussian noises, while others exhibit complex multifractal dynamics. Regarding the source of multifractality, our results are mixed. Time series shuffling produces a reduction in the level of multifractality, but not enough to offset it. We find an association of kurtosis with multifractality.

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  • Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    • Handle: RePEc:arx:papers:2003.09720
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    Cited by:

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    2. Arouxet, M. Belén & Bariviera, Aurelio F. & Pastor, Verónica E. & Vampa, Victoria, 2022. "Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.

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    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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