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Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: A statistical analysis of cryptocurrencies
Authors: Chan, Stephen
Chu, Jeffrey
Nadarajah, Saralees
Osterrieder, Jörg
DOI: 10.21256/zhaw-4793
Published in: Journal of Risk and Financial Management
Volume(Issue): 10
Issue: 12
Issue Date: 2017
Publisher / Ed. Institution: MDPI
ISSN: 1911-8066
Language: English
Subjects: Fintech; Bitcoin; Exchange rates; Cryptocurrencies
Subject (DDC): 332: Financial economics
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 US 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, whilst 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.
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

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