Bitcoin and market-(in)efficiency: a systematic time series approach
Nils Bundi () and
Marc Wildi ()
Additional contact information
Nils Bundi: Stevens Institute of Technology
Marc Wildi: Zurich University of Applied Sciences
Digital Finance, 2019, vol. 1, issue 1, 47-65
Abstract Recently, cryptocurrencies have received substantial attention by investors given their innovative features, simplicity and transparency. We here analyze the increasingly popular Bitcoin and verify pertinence of the efficient market hypothesis. Recent research suggests that Bitcoin markets, while inefficient in their early days, transitioned into efficient markets recently. We challenge this claim by proposing simple trading strategies based on moving average filters, on classic time series models as well as on non-linear neural nets. Our findings suggest that trading performances of our designs are significantly positive; moreover, linear and non-linear approaches perform similarly except at singular time periods of the Bitcoin; finally, our results suggest that markets are becoming less rather than more efficient towards the sample end of the data.
Keywords: Bitcoin; Cryptocurrencies; Efficient market hypothesis; Time series analysis; Moving average filters (search for similar items in EconPapers)
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s42521-019-00004-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:digfin:v:1:y:2019:i:1:d:10.1007_s42521-019-00004-z
Ordering information: This journal article can be ordered from
Access Statistics for this article
Digital Finance is currently edited by Wolfgang Karl Härdle, Steven Kou and Min Dai
More articles in Digital Finance from Springer
Bibliographic data for series maintained by Sonal Shukla ().