Uncertainty and bubbles in cryptocurrencies: Evidence from newly developed uncertainty indices
Md Shahedur R. Chowdhury and
Damian S. Damianov
International Review of Financial Analysis, 2024, vol. 91, issue C
Abstract:
In this paper, we examine whether newly developed crypto price and policy uncertainty indices based on news coverage (Lucey et al., 2022) are associated with the emergence of bubbles in cryptocurrencies. Using probit regressions, we show that these indices have a higher explanatory power than factors previously considered in the literature. Furthermore, using a random forest model, we show that these classifiers are associated with the largest information gain (reduction in the Gini impurity measure) of the model. While the COVID-19 pandemic has exacerbated the occurrence of bubbles, these crypto uncertainty indices remain the best predictors of bubbles both before and during the pandemic. These results are robust to alternative definitions of a bubble, variations in the time horizon, and the inclusion of various regressors known to be related to the price movements in crypto assets.
Keywords: Cryptocurrencies; Bubbles; UCRY Price; UCRY policy; Uncertainty; COVID-19 (search for similar items in EconPapers)
JEL-codes: C32 F3 G15 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521923004659
Full text for ScienceDirect subscribers only
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:eee:finana:v:91:y:2024:i:c:s1057521923004659
DOI: 10.1016/j.irfa.2023.102949
Access Statistics for this article
International Review of Financial Analysis is currently edited by B.M. Lucey
More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().