As we are observing financial markets day by day, we have noticed several repeating patterns. As a result, plenty of seasonality effects can be connected with a specific hour, day in the week/month, or even a more extended period. Regardless of the period, all effects have one common matter: abnormal performance during the timeframe. For example, there might be a large amount of capital that investors seek to allocate that creates upward pressure and stocks rise.
All the aforementioned effects are present in the developed markets that offer a long history either for empirical observations or thorough systematic analysis. Are there any seasonality effects in Bitcoin’s market? Indisputably, the BTC has attracted many, but there is high volatility, and the market is truly dynamic.
One of the most recognized effects relates to the part of the day – the opening of the market, closing auction, overnight anomaly, intraday reversal, and many more daily effects were suggested by academics. However, the cryptocurrency markets are unique, and these crypto assets are traded 24/7. Therefore, there is no “open” or “close” time. Although we can map the hours to when traditional markets are open, cryptos can still be traded outside these hours.
The analysis shows that the hourly distribution of the daily returns is not uniform. There are several periods when the return is relatively small and economically insignificant. Furthermore, there are several hours when the BTC returns are above the average. In particular, the returns for 22:00 and 23:00 (UTC +0) seem to be the most economically significant.

Fundamental reason

Conversely to other widely recognized effects such as the Turn of the month, Payday effect or various strategies connected with rebalancing dates, the reason for the functionality of the BTC seasonality is not that clear. However, the most promising explanation could be connected with the opening hours of the other major markets/exchanges. Interestingly, all major markets are closed during this period. For UTC +0, the NYSE is open during 14:30 and 21:00, Tokyo Stock Exchange is also closed (it is opened from 00:00 to 06:00 of UTC +0 time), Hong Kong is also closed (it is opened from 01:30 to 08:00 of UTC +0 time), same as India (2:30 to 10:00 of UTC +0 time), and Australia is closed too (23:00 to 05:00 of UTC +0 time). Both London and continental Europe are closed during these significant hours since it is night there. Therefore, it seems that the best time to trade (and hold) BTC is when every other major exchange is closed. As a result, the seasonality might be a result of willingness to trade and the BTC market as one of a very few options to do so.
Additionally, based on the hourly return’s distribution, the negative returns are insignificant, while several positive returns are statistically significant on the 5% level. From both statistical and economic points of view, the returns 22:00 and 23:00 dominate.

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Markets Traded

Backtest period from source paper

Confidence in anomaly's validity

Indicative Performance

Notes to Confidence in Anomaly's Validity

Notes to Indicative Performance

data from the text at page 9 (annualized return)

Period of Rebalancing

Estimated Volatility

Notes to Period of Rebalancing

Notes to Estimated Volatility

data from the text at page 9 (annualized return)

Number of Traded Instruments

Maximum Drawdown

Notes to Number of Traded Instruments


Notes to Maximum drawdown

data from the text at page 9 (annualized return)

Complexity Evaluation
Simple strategy

Sharpe Ratio

Notes to Complexity Evaluation


Financial instruments

Simple trading strategy

The investment universe consists of Bitcoin and the data are obtained from Gemini exchange. To exploit the seasonality, open a long position in the BTC at 22:00 (UTC +0) and hold it for two hours. The position is closed after the two hour holding period.

Hedge for stocks during bear markets

No - this long-only strategy is not performing well during bear markets, and cryptocurrencies are one of the riskiest assets to hold during periods of uncertainty.

Source paper
Out-of-sample strategy's implementation/validation in QuantConnect's framework (chart+statistics+code)
Other papers

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