Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

IRTG1792DP2019 020

Rise of the Machines? Intraday High-Frequency Trading Patterns of

Alla A. Petukhina
Raphael C. G. Reule
Wolfgang Karl Härdle

This research analyses high-frequency data of the cryptocurrency market in
regards to intraday trading patterns. We study trading quantitatives such as
returns, traded volumes, volatility periodicity, and provide summary statistics
of return correlations to CRIX (CRyptocurrency IndeX), as well as respective
overall high-frequency based market statistics. Our results provide mandatory
insight into a market, where the grand scale employment of automated trading
algorithms and the extremely rapid execution of trades might seem to be a
standard based on media reports. Our findings on intraday momentum of trading
patterns lead to a new view on approaching the predictability of economic value
in this new digital market.

Cryptocurrency, High-Frequency Trading, Algorithmic Trading, Liquidity,
Volatility, Price Impact, CRIX

JEL Classification:
G02, G11, G12, G14, G15, G23