Long, HuaigangZaremba, AdamDemir, EnderSzczygielski, Jan JakubVasenin, Mikhail2020-10-032020-10-032020-07Long, H.G., Zaremba, A., Demir, E. et al. 2020, 'Seasonality in the cross-section of cryptocurrency returns', Finance Research Letters, vol. 35, art. 101566, pp. 1-8.1544-6123 (print)1544-6131 (online)10.1016/j.frl.2020.101566http://hdl.handle.net/2263/76329This 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.en© 2020 The Authors. This is an open access article under the CC BY-NC-ND license.CryptocurrenciesCross-sectional seasonalityCross-section of returnsReturn predictabilityAsset pricingArticle