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Journal of Financial and Quantitative Analysis Vol. 60 No. 4 2025

Variance Decomposition and Cryptocurrency Return Prediction

Suzanne S. Lee; Minho Wang

College of Business and Technology

open access

Abstract

This article examines how realized variances predict cryptocurrency returns in the cross section using intraday data. We find that cryptocurrencies with higher variances exhibit lower returns in subsequent weeks. Decomposing total variances into signed jump and jump-robust variances reveals that the negative predictability is attributable to positive jump and jump-robust variances. The negative pricing effect is more pronounced for smaller cryptocurrencies with lower prices, less liquidity, more retail trading activities, and more positive sentiment. Our results suggest that cryptocurrency markets are unique because retail investors and preferences for lottery-like payoffs play important roles in the partial variance effects.

DOI
10.1017/s002210902400022x
Volume
60
Issue
4
Pages
1859-1890
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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