Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach

Kun Duan, Zeming Li, Andrew Urquhart and Jinqiang Ye

International Review of Financial Analysis, 2021, vol. 75, issue C

Abstract: Employing a long-memory approach, we provide a study of the evolution of informational efficiency in five major Bitcoin markets and its influence on cross-market arbitrage. While all the markets are close to full informational efficiency over the whole sample period, the degree of market efficiency varies across markets and over time. The cross-market discrepancy in market efficiency gradually vanishes, suggesting the segmented markets are developing to a consensus where all markets are equally efficient. Through a fractionally cointegrated vector autoregressive (FCVAR) model we show that when the efficiency in Bitcoin/USD and Bitcoin/AUD markets improves the cross-market arbitrage potential narrows, whereas it widens when the efficiency in Bitcoin/CAD, Bitcoin/EUR, and Bitcoin/GBP markets improves. A battery of robustness checks reassure our main findings.

Keywords: Bitcoin; Market efficiency; Cryptocurrency; Long memory; FCVAR (search for similar items in EconPapers)
JEL-codes: G14 G15 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521921000685
Full text for ScienceDirect subscribers only

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:eee:finana:v:75:y:2021:i:c:s1057521921000685

DOI: 10.1016/j.irfa.2021.101725

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().