Seasonality in the Cross-Section of Cryptocurrency Returns

Huaigang Long · Adam Zaremba · Ender Demir · Jan Jakub Szczygielski · Mikhail Vasenin

49 citations0/0 files storedFinance research letters

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Financial Markets and Investment Strategies FinTech, Crowdfunding, Digital Finance Stock Market Forecasting Methods

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 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.

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References

1997On Persistence in Mutual Fund Performance 1973Risk, Return, and Equilibrium: Empirical Tests 2002Illiquidity and stock returns: cross-section and time-series effects 1998Alternative factor specifications, security characteristics, and the cross-section of expected stock returns1We are especially grateful to Eugene Fama (a referee), an anonymous referee and Bill Schwert (the editor) for insightful and constructive suggestions. We also thank Wayne Ferson, Ken French, Will Goetzmann, Craig Holden, Ravi Jagannathan, Bob Jennings, Bruce Lehmann, Josef Lakonishok, Richard Roll, participants at the 1997 Meetings of the Western Finance Association, the 1997 UCLA/USC/UC Irvine conference, the November 1997 Asset Pricing Meeting of the National Bureau of Economic Research, the Atlanta Forum, and seminars at Columbia, Indiana, Florida, New York, Tulane, and Yale Universities; Eugene Fama and Ken French for providing part of the data used in this study; and Christoph Schenzler for excellent programming assistance. The second author acknowledges support from the Dean's Fund for Research and the Financial Markets Research Center at Vanderbilt University. We are responsible for remaining errors. This paper was formerly titled `A Re-Examination of Security Return Anomalies'.1 2022Common Risk Factors in Cryptocurrency 2018Liquidity and market efficiency in cryptocurrencies 2007Seasonality in the cross-section of stock returns☆2018Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero

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