Bitcoin’s holiday effect

Nakamoto 2025-10-31 17:37 17837人围观 BTC

Today I will share an article on the application of the calendar effect in timing strategies on Bitcoin. 1 Research background Holiday effect in traditional markets: There is a "holiday effect" in traditional stock and commodity markets, that is, trading

Today I share an article on the application of the calendar effect in timing strategies on Bitcoin.

1 Research background

Holiday effect in traditional markets: There is a "holiday effect" in traditional stock and commodity markets, that is, trading days before public holidays tend to perform better than other trading days.

This effect was first discovered by Ariel (1990) and verified by Kim and Park (1994) in multiple markets including the New York Stock Exchange, Nasdaq, and the FTSE 30 Index.
Quantpedia classifies this anomaly as one of the most significant calendar effects, reporting that the average return on pre-holiday trading days is more than ten times that of other ordinary trading days.

In behavioral finance, the calendar effect is classified as driven by emotions and attention biases. However, the Bitcoin market has some special characteristics: the Bitcoin market has extremely high volatility, a higher proportion of retail investors, and is mainly affected by some non-traditional information flows.

This article mainly discusses:

Does the classic pre-holiday effect apply to cryptocurrencies?
Does the attention-grabbing momentum filter based on local price highs work on Bitcoin?

2 Methodology and data sources

Data source:

Using the daily closing price of Bitcoin from January 2018 to June 2025, the data comes from an internal database (2018-2021 for futures and 2021-2025 for the ETF itself). The BITO ETF (which tracks Bitcoin futures) was chosen over other spot Bitcoin ETFs (such as IBIT, GBTC or FBTC) or spot Bitcoin itself because the data is only considered meaningful for backtesting since the launch of regulated Bitcoin futures in 2018.

Public holidays (publib holidays):

Considering that U.S. holidays have a certain impact on global stock markets, they should also have an impact on the cryptocurrency market. Therefore, the final definition is based on the US calendar, referring to the Time and Date website.

Trading strategy:

Since the ProShares Bitcoin ETF (BITO) trades on U.S. exchanges but cannot trade on the day of the holiday (D0), long Bitcoin positions are always held during the holiday, thereby capturing the effect of attention bias.

3 Holiday window analysis

The analysis range starts from the 5 trading days before each holiday (D-5) and ends with the 5 trading days after the holiday (D+5).

Bitcoin holiday yield distribution

It can be seen that the overall yield is higher before holidays, so we construct the following strategy:

Buy cryptocurrency the day before the holiday (D-1), hold it until the holiday is over, and close the position at the close of the day after the holiday (D+1). The net value curve of this strategy shows the investment income. The return rate of the strategy is not high. Most of the time, the short position goes flat. Therefore, it is still necessary to find other solutions to enhance the return of the strategy.

4 Attention Enhancement Strategies

Combined with a momentum filter: During the holidays, retail investors usually have more free time and are more inclined to participate in financial markets out of curiosity or even boredom. If cryptocurrency prices break out to new short-term highs during this period, additional attention and speculation from retail investors may push prices higher. Essentially, the combination of bullish technical signals and high retail activity during the holiday season could fuel a bullish move, creating a repeatable and potentially profitable trading pattern.
N-day high filter: Define a filter on the day when the closing price of BTC exceeds the highest closing price of the previous N trading days (N ∈ {5, 10, 20}). Then identify dates that are both in the holiday window (D-5 to D+5) and meet the N-day high condition. For each qualifying day, the position is opened at the close and closed at the close of the next trading day.

From the histogram, compared with the above figure which only considers the holiday effect, under different lookback days N, the average return rate from D-1 to D+1 is significantly positive.

Therefore, N under three different parameters is used to construct the strategy. The position window is D-1 to D+1, and the net value is as follows:

Net value of strategy under different N-day high filter+holiday drift

The main performance indicators of the strategy are as follows:

The 5-day lookback window performed best, but at the expense of the highest volatility and largest drawdowns, nonetheless with a Sharpe ratio of over 0.6 and a Kalmar ratio of over 0.7, it looks quite attractive.

5 Discussion and conclusion

Bitcoin exhibits a similar pre-holiday drift to the stock market, but only when combined with short-term momentum triggers. As a proxy for market attention, the N-day high filter captures samples of both retail and institutional investors facing this specific trading time and positive feedback situation at the same time. This synergy produces robust risk-adjusted returns.

6 Statement

This article is for academic communication only and does not constitute any investment advice.
Any losses caused by referring to this article must be borne by the author and has nothing to do with it.