Bitcoin at high frequency

Artikel

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 h. 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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 12 ; Year: 2019 ; Issue: 1 ; Pages: 1-20 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft
• Thema: bitcoin ; realized volatility ; HAR ; high frequency

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Catania, Leopoldo ; Sandholdt, Mads
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2019

Weitere Informationen

• DOI: doi:10.3390/jrfm12010036
• Handle: http://hdl.handle.net/10419/239021
• Letzte Aktualisierung: 20.09.2024, 08:24 MESZ