Abstract
ABSTRACT Despite the growing literature on Bitcoin and other cryptocurrencies, we know relatively little about who are involved in trading, transacting and using these assets and how they behave. Examining millions of Bitcoin transaction records, we show that less than 1% of Bitcoin users contribute to more than 95% of the market volumes. These ‘whales’ are often associated with strategic trading/transaction volumes, market reactions and timing patterns. Using K-means clustering on a comprehensive transaction dataset, we establish a typology of traders by learning their trading exchange patterns, strategies and impact risk and market microstructure. Our approach ‘learns’ and identifies five distinct groups or types of Bitcoin users, which are somewhat, though not entirely, comparable to popular categorisations used in conventional market such as fundamental, technical, retail and institutional traders as well as market makers. Four of these groups present distinguishable trading patterns with a strong impact on liquidity provision and trading signals.
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