High Frequency Volatility Co-Movements in Cryptocurrency Markets

31 Pages Posted: 24 Sep 2019

See all articles by Paraskevi Katsiampa

Paraskevi Katsiampa

Sheffield University Management School

Shaen Corbet

Dublin City University ; University of Waikato - Management School

Brian M. Lucey

Trinity Business School, Trinity College Dublin; Ho Chi Minh City University of Economics and Finance; Jiangxi University of Finance and Economics

Date Written: September 15, 2019

Abstract

Through the application of Diagonal BEKK and Asymmetric Diagonal BEKK methodologies to intra-day data for eight cryptocurrencies, this paper investigates not only conditional volatility dynamics of major cryptocurrencies, but also their volatility co-movements. We first provide evidence that all conditional variances are significantly affected by both previous squared errors and past conditional volatility. It is also shown that both methodologies indicate that cryptocurrency investors pay the most attention to news relating to Neo and the least attention to news relating to Dash, while shocks in OmiseGo persist the least and shocks in Bitcoin persist the most, although all of the considered cryptocurrencies possess high levels of persistence of volatility over time. We also demonstrate that the conditional covariances are significantly affected by both cross-products of past error terms and past conditional covariances, suggesting strong interdependencies between cryptocurrencies. It is also demonstrated that the Asymmetric Diagonal BEKK model is a superior choice of methodology, with our results suggesting significant asymmetric effects of positive and negative shocks in the conditional volatility of the price returns of all of our investigated cryptocurrencies, while the conditional covariances capture asymmetric effects of good and bad news accordingly. Finally, it is shown that time-varying conditional correlations exist, with our selected cryptocurrencies being strongly positively correlated, further highlighting interdependencies within cryptocurrency markets.

Keywords: Cryptocurrencies; High-frequency data; Asymmetric Diagonal BEKK; MGARCH; Volatility

Suggested Citation

Katsiampa, Paraskevi and Corbet, Shaen and Lucey, Brian M., High Frequency Volatility Co-Movements in Cryptocurrency Markets (September 15, 2019). Available at SSRN: https://ssrn.com/abstract=3454217 or http://dx.doi.org/10.2139/ssrn.3454217

Paraskevi Katsiampa

Sheffield University Management School ( email )

17 Mappin Street
Sheffield, Sheffield S1 4DT
United Kingdom

Shaen Corbet (Contact Author)

Dublin City University ( email )

Dublin 9
Ireland

University of Waikato - Management School ( email )

Hamilton
New Zealand

Brian M. Lucey

Trinity Business School, Trinity College Dublin ( email )

The Sutherland Centre, Level 6, Arts Building
Dublin 2
Ireland
+353 1 608 1552 (Phone)
+353 1 679 9503 (Fax)

Ho Chi Minh City University of Economics and Finance ( email )

59C Nguyen Dình Chieu
6th Ward, District 3
Ho Chi Minh City, Ho Chi Minh 70000
Vietnam

Jiangxi University of Finance and Economics ( email )

South Lushan Road
Nanchang, Jiangxi 330013
China

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