Time-varying long-term memory in Bitcoin market

Yonghong Jiang, He Nie and Weihua Ruan

Finance Research Letters, 2018, vol. 25, issue C, 280-284

Abstract: This study attempts to investigate the time-varying long-term memory in the Bitcoin market through a rolling window approach and by employing a new efficiency index (Sensoy and Hacihasanoglu, 2014). The daily dataset for the period from 2010 to 2017 is utilized, and some interesting findings emerge that: (i) all of the generalized Hurst exponents in the Bitcoin market are above 0.5; (ii) long-term memory exists in the Bitcoin market; (iii) high degree of inefficiency ratio; (iv) the Bitcoin market does not become more efficient over time; and (v) rolling window approach can help to obtain more reliable results. Some implications for investors and policymakers are concluded.

Keywords: Long-term memory; Bitcoin market; Generalized Hurst exponents; Rolling window (search for similar items in EconPapers)
JEL-codes: C65 G14 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (114)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612317306682
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:finlet:v:25:y:2018:i:c:p:280-284

DOI: 10.1016/j.frl.2017.12.009

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().