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A Statistical Analysis of Cryptocurrencies

School of Mathematics, University of Manchester, Manchester M13 9PL, UK
School of Engineering, Zurich University of Applied Sciences, 8401 Winterthur, Switzerland
Author to whom correspondence should be addressed.
Academic Editor: Charles S. Tapiero
J. Risk Financial Manag. 2017, 10(2), 12;
Received: 7 April 2017 / Revised: 23 May 2017 / Accepted: 27 May 2017 / Published: 31 May 2017
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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. View Full-Text
Keywords: exchange rate; distributions; blockchain; Bitcoin exchange rate; distributions; blockchain; Bitcoin

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Chan, S.; Chu, J.; Nadarajah, S.; Osterrieder, J. A Statistical Analysis of Cryptocurrencies. J. Risk Financial Manag. 2017, 10, 12.

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J. Risk Financial Manag. EISSN 1911-8074 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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