Seasonality in the Cross-Section of Cryptocurrency Returns

Huaigang Long, Adam Zaremba*, Ender Demir, Jan Jakub Szczygielski, Mikhail Vasenin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)
137 Downloads (Pure)


This study presents the first attempt to examine the cross-sectional seasonality anomaly in cryptocurrency markets. To this end, we apply sorts and cross-sectional regressions to investigate daily returns on 151 cryptocurrencies for the years 2016 to 2019. We find a significant seasonal pattern: average past same-weekday returns positively predict future performance in the cross-section. Cryptocurrencies with high same-day returns in the past outperform cryptocurrencies with a low same-day return. This effect is not subsumed by other established return predictors such as momentum, size, beta, idiosyncratic risk, or liquidity.

Original languageEnglish
Article number101566
JournalFinance Research Letters
Early online date12 May 2020
Publication statusPublished - 1 Jul 2020


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