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A Statistical Analysis of Cryptocurrencies

Author

Listed:
  • Stephen Chan

    () (School of Mathematics, University of Manchester, Manchester M13 9PL, UK)

  • Jeffrey Chu

    () (School of Mathematics, University of Manchester, Manchester M13 9PL, UK)

  • Saralees Nadarajah

    () (School of Mathematics, University of Manchester, Manchester M13 9PL, UK)

  • Joerg Osterrieder

    () (School of Engineering, Zurich University of Applied Sciences, 8401 Winterthur, Switzerland)

Abstract

We analyze statistical properties of the largest cryptocurrencies (determined by market capitalization), of which Bitcoin is the most prominent example. We characterize their exchange rates versus the U.S. Dollar by fitting parametric distributions to them. It is shown that returns are clearly non-normal, however, no single distribution fits well jointly to all the cryptocurrencies analysed. We find that for the most popular currencies, such as Bitcoin and Litecoin, the generalized hyperbolic distribution gives the best fit, while for the smaller cryptocurrencies the normal inverse Gaussian distribution, generalized t distribution, and Laplace distribution give good fits. The results are important for investment and risk management purposes.

Suggested Citation

  • Stephen Chan & Jeffrey Chu & Saralees Nadarajah & Joerg Osterrieder, 2017. "A Statistical Analysis of Cryptocurrencies," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 10(2), pages 1-23, May.
  • Handle: RePEc:gam:jjrfmx:v:10:y:2017:i:2:p:12-:d:100126
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    References listed on IDEAS

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    1. repec:eee:phsmap:v:505:y:2018:i:c:p:1069-1074 is not listed on IDEAS

    More about this item

    Keywords

    exchange rate; distributions; blockchain; Bitcoin;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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