Extreme Correlation in Cryptocurrency Markets

32 Pages Posted: 29 May 2018 Last revised: 10 Mar 2023

See all articles by Konstantinos Gkillas

Konstantinos Gkillas

Hellenic Mediterranean University

Costas Siriopoulos

Zayed University, College of Business; University of Patras - Business Administration

Date Written: November 3, 2018

Abstract

In this paper, we study the contemporaneous tail dependence structure in a pairwise comparison of the ten largest cryptocurrencies, namely Bitcoin, Dash, Dogecoin, Ethereum, Litecoin, Monero, Namecoin, Novacoin, Peercoin, and Ripple. We apply multivariate extreme value theory and we estimate a bias-corrected extreme correlation coefficient. Our findings reveal clear patterns of significantly high bivariate dependency in the distribution tails of some of the most basic and widespread cryptocurrencies, primarily over various downside constraints. This means that extreme correlation is not related to cryptocurrency market volatility per se, but to the trend of the cryptocurrency market. Therefore, extreme correlation increases in bear markets, but not in bull markets for these pairs. Interestingly, there is also a significant number of pairs which exhibit a weak level of dependency in distribution tails.

Keywords: Bitcoin; cryptocurrencies; extremes; tail dependence; downside risk

JEL Classification: C46; F38; G01

Suggested Citation

Gkillas, Konstantinos and Siriopoulos, Costas, Extreme Correlation in Cryptocurrency Markets (November 3, 2018). Available at SSRN: https://ssrn.com/abstract=3180934 or http://dx.doi.org/10.2139/ssrn.3180934

Konstantinos Gkillas (Contact Author)

Hellenic Mediterranean University ( email )

Estavromenos
Heraklion, 71410
Greece

HOME PAGE: http://www.gillas.gr

Costas Siriopoulos

Zayed University, College of Business ( email )

P.O. Box 144534
Abu Dhabi
United Arab Emirates

University of Patras - Business Administration ( email )

Patras
Greece

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