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J. Risk Financial Manag. 2019, 12(1), 36; https://doi.org/10.3390/jrfm12010036

Bitcoin at High Frequency

1
Department of Economics and Business Economics, Aarhus University and CREATES, Aarhus BSS, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark
2
Tvilum A/S, Egon Kristiansens Allé 2, DK-8882 Faarvang, Denmark
*
Author to whom correspondence should be addressed.
Received: 12 December 2018 / Revised: 23 January 2019 / Accepted: 30 January 2019 / Published: 15 February 2019
(This article belongs to the Special Issue Alternative Assets and Cryptocurrencies)
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Abstract

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. View Full-Text
Keywords: bitcoin; realized volatility; HAR; high frequency bitcoin; realized volatility; HAR; high frequency
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Catania, L.; Sandholdt, M. Bitcoin at High Frequency. J. Risk Financial Manag. 2019, 12, 36.

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