Crypto market dynamics in stressful conditions

Christophe Desagre, Paolo Mazza and Mikael Petitjean

Applied Economics, 2023, vol. 55, issue 27, 3121-3153

Abstract: Understanding market liquidity and trading dynamics in one of the most innovative and volatile markets in the world, is crucial from the standpoint of both regulators and investors. In contrast to stocks, very little is known about the functioning of cryptos around extreme returns (ERs). Using high-frequency order-book and trade data for the 8 most widespread cryptos on 16 trading platforms over three years, we examine the contemporaneous and lagged influence of trading activity and liquidity on the occurrence of extreme returns (ERs) in a logistic regression framework adapted to rare events. Despite its huge volatility, we show that the trading and liquidity dynamics on the crypto market around ERs is not orthogonal to what traditional markets experience in stressful conditions. The number of trades is a particularly robust driver to explain the occurrence of ERs, followed by the relative spread. The same drivers are identified for traditional markets.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2022.2108754 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Crypto market dynamics in stressful conditions (2023)
Working Paper: Crypto market dynamics in stressful conditions (2023)
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:27:p:3121-3153

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2022.2108754

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 ().