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Intraday volume-return nexus in cryptocurrency markets:: novel evidence from cryptocurrency classification.

Intraday volume-return nexus in cryptocurrency markets:: novel evidence from cryptocurrency classification.
Intraday volume-return nexus in cryptocurrency markets:: novel evidence from cryptocurrency classification.
This paper analyses the volume-return relationships across the top 30 most traded cryptocurrencies from April 2013 to June 2019 using high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as geographical location of headquarters, founder and founder’s origin, platform on which the cryptocurrency is built, and consensus algorithm, among others. We identify significant bidirectional causalities between trading volume and returns at different high-frequency intervals; however, those linkages are weakening with decreasing data frequencies. The findings confirm the leading position of the Bitcoin trading volume in the cryptocurrency price formation. This evidence will help investors to design effective trading strategies in cryptocurrency markets providing useful insights from cryptocurrency categorisation.
cryptocurrency classification, volume-return relationships, Granger causality
0275-5319
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
Zięba, Damian
573b2a9a-d67c-41e6-8e60-fa99000aea0f
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
Zięba, Damian
573b2a9a-d67c-41e6-8e60-fa99000aea0f

Yarovaya, Larisa and Zięba, Damian (2021) Intraday volume-return nexus in cryptocurrency markets:: novel evidence from cryptocurrency classification. Research in International Business and Finance, 60, [101592]. (doi:10.1016/j.ribaf.2021.101592).

Record type: Article

Abstract

This paper analyses the volume-return relationships across the top 30 most traded cryptocurrencies from April 2013 to June 2019 using high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as geographical location of headquarters, founder and founder’s origin, platform on which the cryptocurrency is built, and consensus algorithm, among others. We identify significant bidirectional causalities between trading volume and returns at different high-frequency intervals; however, those linkages are weakening with decreasing data frequencies. The findings confirm the leading position of the Bitcoin trading volume in the cryptocurrency price formation. This evidence will help investors to design effective trading strategies in cryptocurrency markets providing useful insights from cryptocurrency categorisation.

Text
Yarovaya and Zieba Trading volumes REVISED - Accepted Manuscript
Restricted to Repository staff only until 6 December 2023.
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More information

Accepted/In Press date: 29 November 2021
e-pub ahead of print date: 6 December 2021
Keywords: cryptocurrency classification, volume-return relationships, Granger causality

Identifiers

Local EPrints ID: 453260
URI: http://eprints.soton.ac.uk/id/eprint/453260
ISSN: 0275-5319
PURE UUID: b181b585-1d29-41bb-bf10-914862672940
ORCID for Larisa Yarovaya: ORCID iD orcid.org/0000-0002-9638-2917

Catalogue record

Date deposited: 11 Jan 2022 17:48
Last modified: 12 Jan 2022 02:54

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Contributors

Author: Larisa Yarovaya ORCID iD
Author: Damian Zięba

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