Cryptocurrency bubbles, information asymmetry and noise trading

Purpose This paper examines the relationship between the degree of information asymmetry among investors and the occurrence of bubbles in cryptocurrency markets. Design/methodology/approach The study applies the Philipps, Shi and Yu (PSY) methodology to identify bubbles in 74 cryptocurrencies from July 2014 to April 2021. Findings The findings indicate that there is a negative relationship between the degree of information asymmetry among investors and the number and duration of bubbles across cryptocurrencies. Originality/value This finding supports the riding-bubble argument of Asako et al. (2020), which suggests that when the information asymmetry among investors is high, rational investors are less certain about what irrational, inexperienced investors might decide. This strategic uncertainty leads rational investors to close out their positions more quickly, resulting in a shorter duration of the bubble and a reduced propensity for new bubbles to emerge. The study’s findings hold regardless of the proxies used to measure information asymmetry and noise trading, cryptocurrency characteristics and regression model specifications.

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Publication Details

Journal
The Journal of Risk Finance
Published
2025-02-07
DOI
https://doi.org/10.1108/jrf-07-2024-0220
Citations
7
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
21.92
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article

Cryptocurrency bubbles, information asymmetry and noise trading

Geoffroy Enjolras, Élise Alfieri, Radu Burlacu
7 citations
The Journal of Risk Finance
Complex Systems and Time Series Analysis
21.92
article

Cryptocurrency bubbles, information asymmetry and noise trading

Geoffroy Enjolras, Élise Alfieri, Radu Burlacu
article en
7 citations

Abstract

Purpose This paper examines the relationship between the degree of information asymmetry among investors and the occurrence of bubbles in cryptocurrency markets. Design/methodology/approach The study applies the Philipps, Shi and Yu (PSY) methodology to identify bubbles in 74 cryptocurrencies from July 2014 to April 2021. Findings The findings indicate that there is a negative relationship between the degree of information asymmetry among investors and the number and duration of bubbles across cryptocurrencies. Originality/value This finding supports the riding-bubble argument of Asako et al. (2020), which suggests that when the information asymmetry among investors is high, rational investors are less certain about what irrational, inexperienced investors might decide. This strategic uncertainty leads rational investors to close out their positions more quickly, resulting in a shorter duration of the bubble and a reduced propensity for new bubbles to emerge. The study’s findings hold regardless of the proxies used to measure information asymmetry and noise trading, cryptocurrency characteristics and regression model specifications.

The Journal of Risk FinanceVol. 26(2)
Institut polytechnique de Grenoble (FR), Université Paris-Est Créteil (FR), Centre d'Etudes et de Recherches Appliquées à la Gestion (FR), Université Gustave Eiffel (FR), Institut de Recherche en Gestion (FR), Université Grenoble Alpes (FR)
Openalex Percentile: Top 1%
Complex Systems and Time Series Analysis
21.92
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Cryptocurrency bubbles, information asymmetry and noise trading — Geoffroy Enjolras, Élise Alfieri, et al. · The Journal of Risk Finance (2025) | TGRS Research Map | TGRS