Topological recognition of critical transitions in time series of cryptocurrencies

Marian Gidea, Daniel Goldsmith, Yuri Katz, Pablo Roldan and Yonah Shmalo

Physica A: Statistical Mechanics and its Applications, 2020, vol. 548, issue C

Abstract: We analyze four major cryptocurrencies (Bitcoin, Ethereum, Litecoin, and Ripple) before the digital asset market crash at the beginning of 2018. We also analyze Bitcoin before some of the mini-crashes that occurred during the period 2016–2018. All relevant time series exhibited a highly erratic behavior.

Keywords: Cryptocurrency; Critical transitions; Complex systems dynamics; Topological data analysis; Financial time series; k-means clustering (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119321363
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:phsmap:v:548:y:2020:i:c:s0378437119321363

DOI: 10.1016/j.physa.2019.123843

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().