GARCH Modelling of Cryptocurrencies
Jeffrey Chu,
Stephen Chan,
Saralees Nadarajah and
Joerg Osterrieder
Additional contact information
Jeffrey Chu: School of Mathematics, University of Manchester, Manchester M13 9PL, U.K.
Stephen Chan: Department of Mathematics and Statistics, American University of Sharjah, Sharjah P.O. Box 26666, UAE
Saralees Nadarajah: School of Mathematics, University of Manchester, Manchester M13 9PL, U.K.
Joerg Osterrieder: School of Engineering, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland
JRFM, 2017, vol. 10, issue 4, 1-15
Abstract:
With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates.
Keywords: exchange rate; maximum likelihood; value at risk (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (150)
Downloads: (external link)
https://www.mdpi.com/1911-8074/10/4/17/pdf (application/pdf)
https://www.mdpi.com/1911-8074/10/4/17/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:10:y:2017:i:4:p:17-:d:113895
Access Statistics for this article
JRFM is currently edited by Ms. Chelthy Cheng
More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().