Seasonality in the Cross-Section of Cryptocurrency Returns

Long H., Zaremba A., DEMİR E. , Szczygielski J. J. , Vasenin M.

FINANCE RESEARCH LETTERS, cilt.35, 2020 (SSCI İndekslerine Giren Dergi) identifier identifier


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 crosssection. 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.