Bitcoin Posts Strongest Next-Day Gains on U.S. Holidays
A CoinGecko study of May 2013–May 2026 finds New Year’s Day produced an average next-day gain of +2.01% with an 84.6% win rate; holidays averaged +0.77% vs +0.19% on non-holidays.
A CoinGecko study covering May 2013 through May 2026 found Bitcoin posted its largest average next-day returns on U.S. federal holidays. The dataset included 4,753 daily price observations. New Year’s Day had an average next-day return of +2.01% and an 84.6% win rate. Overall, federal holidays delivered an average next-day gain of +0.77%, compared with +0.19% on non-holiday days.
The study found the holiday effect persisted as Bitcoin traded at very different prices, from about $313 in 2015 to roughly $93,507 in 2025. CoinGecko’s analysis connects the New Year’s Day signal to fresh capital entering markets in January and to reversals of December tax-loss selling.
Several holidays showed strong average next-day returns. Columbus Day matched New Year’s Day with an 84.6% win rate and an average next-day return of +1.70%. Christmas Day averaged a +1.46% return the following day with a 53.8% win rate. Labor Day recorded an average next-day gain of +1.22% and a 69.2% win rate.
Two federal holidays showed negative average next-day returns. Martin Luther King Jr. Day averaged -0.84% next-day returns, a figure heavily influenced by an 18.65% decline in Bitcoin on Jan. 15, 2018. Independence Day averaged -0.26% on the next day. Both holidays had win rates below 50%.
The report also examined weekday patterns. Monday and Wednesday tied with average next-day returns of +0.38%. Thursday was the only weekday with a negative average next-day return, at -0.09%. The difference between weekday and weekend returns was 0.01%. Over a 365-day horizon, average returns by weekday ranged from 142.15% to 144.56%.
CoinGecko’s researchers said the data suggest timing around U.S. federal holidays may offer a short-term statistical edge, but the report did not provide trading recommendations. The study noted uncertainty about whether seasonal patterns will repeat in future years.








