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Scaling properties of extreme price fluctuations in Bitcoin markets

Author

Listed:
  • Stjepan Beguv{s}i'c
  • Zvonko Kostanjv{c}ar
  • H. Eugene Stanley
  • Boris Podobnik

Abstract

Detection of power-law behavior and studies of scaling exponents uncover the characteristics of complexity in many real world phenomena. The complexity of financial markets has always presented challenging issues and provided interesting findings, such as the inverse cubic law in the tails of stock price fluctuation distributions. Motivated by the rise of novel digital assets based on blockchain technology, we study the distributions of cryptocurrency price fluctuations. We consider Bitcoin returns over various time intervals and from multiple digital exchanges, in order to investigate the existence of universal scaling behavior in the tails, and ascertain whether the scaling exponent supports the presence of a finite second moment. We provide empirical evidence on slowly decaying tails in the distributions of returns over multiple time intervals and different exchanges, corresponding to a power-law. We estimate the scaling exponent and find an asymptotic power-law behavior with 2

Suggested Citation

  • Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar & H. Eugene Stanley & Boris Podobnik, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Papers 1803.08405, arXiv.org.
  • Handle: RePEc:arx:papers:1803.08405
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    File URL: http://arxiv.org/pdf/1803.08405
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin Technical Trading with Articial Neural Network," CIRJE F-Series CIRJE-F-1090, CIRJE, Faculty of Economics, University of Tokyo.
    2. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating cryptocurrency prices using machine learning," Papers 1805.08550, arXiv.org, revised Oct 2018.

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