Leopoldo Catania

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and volatility intensity at Thursdays and Fridays. We find no predictability for Bitcoin returns at or above one day, though, we find predictability for sample frequencies up to 6 hours. Predictability of Bitcoin returns is also found to be time-varying. We also study the behaviour of the realized volatility of Bitcoin. We document a remarkable high percentage of jumps above 80%. We also find that realized volatility exhibits: i) long memory, ii) leverage effect, and iii) no impact from lagged jumps. A forecast study shows that: i) Bitcoin volatility has become more easy to predict after 2017, ii) including a leverage component helps in volatility prediction, and iii) prediction accuracy depends on the length of the forecast horizon