The Quarter-Hour Effect: Periodic Algorithmic Trading and Return Predictability in Cryptocurrency Futures
Chan Kim, Peter Reinhard Hansen
Abstract
Cryptocurrency markets exhibit periodic bursts in volatility and volume at one-, five-, and quarter-hour marks. Using trade data for six Binance perpetual contracts, we associate these bursts with algorithmic trading: trade-size roundness declines sharply within them, a behavioral signature of algorithmic participation. The Autocorrelation Map, a clock-phase-resolved display, reveals serial dependence in order flow and returns at the quarter-hour openings that conventional measures conceal. This opening activity is not only predictable out of sample but also informative: its order imbalance forecasts four-to-twelve-hour returns, weaker at finer marks. Our results characterize periodic algorithmic trading and its cross-frequency variation.
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