Long, Huaigang, Zaremba, Adam, Demir, Ender, Szczygielski, Kuba and Vasenin, Mikhail (2020) Seasonality in the Cross-Section of Cryptocurrency Returns. Finance Research Letters, 35. p. 101566. ISSN 1544-6123
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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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Cryptocurrencies, Cross-sectional seasonality, Cross-section of returns, Return predictability, Asset pricing |
| Subjects: | N100 Business studies N300 Finance N400 Accounting |
| Department: | Faculties > Business and Law > Newcastle Business School |
| Depositing User: | Elena Carlaw |
| Date Deposited: | 23 Jun 2020 09:21 |
| Last Modified: | 31 Jul 2021 11:32 |
| URI: | http://nrl.northumbria.ac.uk/id/eprint/43547 |
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