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A Statistical Analysis of Cryptocurrencies

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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

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. View Full-Text

Keywords: exchange rate; distributions; blockchain; Bitcoin exchange rate; distributions; blockchain; Bitcoin

Autor: Stephen Chan 1, Jeffrey Chu 1, Saralees Nadarajah 1,* and Joerg Osterrieder 2

Fuente: http://mdpi.com/


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