The tail dependence structure between return and trading volume: an investigation on the Bitcoin market
Kuang-Liang Chang
Applied Economics, 2023, vol. 55, issue 11, 1234-1246
Abstract:
This research assesses the diversification patterns for tail dependence between Bitcoin return and trading volume by utilizing a dynamic mixture copula approach with spillover effect and asymmetric volatility effect. There are four main empirical findings. First, the spillover effect between return and trading volume exists. Second, the leverage effect is statistically significant for return and trading volume. Third, the linkages between return and trading volume are diversified. Both positive and negative tail dependence structures are observed, and the frequency of a positive tail dependence occurring is higher. Furthermore, the asymmetric tail dependence structure exists in positive and negative dependence situations. In the positive dependence structure, a co-movement in the increasing direction is stronger than a co-movement in the decreasing direction. In the negative dependence structure, a situation of a large return with low volume occurs more often than a situation of a small return with high volume. Fourth, the volatility of trading volume positively predicts the magnitude of positive dependence.
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2022.2096870 (text/html)
Access to full text is restricted to subscribers.
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:taf:applec:v:55:y:2023:i:11:p:1234-1246
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2022.2096870
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().