TL;DR
This paper investigates high-frequency cryptocurrency trading data to identify intraday patterns, revealing the influence of algorithmic trading and providing insights into market predictability and volatility.
Contribution
It offers a detailed analysis of intraday trading patterns and their implications for market behavior, highlighting the role of automated trading algorithms in cryptocurrencies.
Findings
Identification of intraday momentum patterns
Insights into the impact of algorithmic trading
Quantitative analysis of return correlations
Abstract
This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market. 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 with respect to temporal aspects. 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 quantitative view on approaching the predictability of economic value in this new digital market.
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