Behavioural Fingerprint of Bitcoin-traders

Behavioural Fingerprint of Bitcoin-traders

Date: Thursday 13 January 2022, 12.00PM
Location: Online
Online - joining instructions will be sent to those registered
Special Interests Group Meeting

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Speaker: Professor Maggie Chen (Cardiff University)

Although Bitcoin has grown to be the largest and best-known cryptocurrency, we still have fairly limited deep understanding about it, in particular, the behavioural fingerprint of Bitcoin traders. In this paper, we examine a complete set of Bitcoin transactions to study the features and activities of Bitcoin traders. Using K-means clustering analysis, among other approaches, we establish a typology of traders by learning their trading patterns and drawing upon trader classifications in mainstream finance such as informed vs. uninformed, retail vs. institutional, small vs large traders and similar categories. The distinguished trader types are often highly indicative of the traders’ specific strategy, behavior and impact on risk and market structure. 

Mining through millions of transaction records, we find that less than 1 percent of Bitcoin traders contribute to more than 95 percent of the market`s trading volume. These Bitcoin whales often demonstrate irregular trading volumes, size and timing patterns. In addition, we are able to propose five distinctive trader types and three of them present unique trading behavior patterns that could be highly indicative to the market.

Professor Maggie Chen (Cardiff University)
Jia Shao for RSS Finance & Economics Special Interest Group