Seasonality in the Cross-Section of Cryptocurrency Returns

【Author】 Long, Huaigang; Zaremba, Adam; Demir, Ender; Szczygielski, Jan Jakub; Vasenin, Mikhail

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【Abstract】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.

【Keywords】Cryptocurrencies; Cross-sectional seasonality; Cross-section of returns; Return predictability; Asset pricing

【发表时间】2020 JUL

【收录时间】2022-01-02

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