Stranger Danger? Investor Behavior and Incentives on Cryptocurrency Copy-Trading Platforms

要旨

Several large financial trading platforms have recently begun implementing ``copy trading,'' a process by which a leader allows copiers to automatically mirror their trades in exchange for a share of the profits realized. While it has been shown in many contexts that platform design considerably influences user choices---users tend to disproportionately trust rankings presented to them---we would expect that here, copiers exercise due diligence given the money at stake, typically USD 500--2\,000 or more. We perform a quantitative analysis of two major cryptocurrency copy-trading platforms, with different default leader ranking algorithms. One of these platforms additionally changed the information displayed during our study. In all cases, we show that the platform UI significantly influences copiers' decisions. Besides being sub-optimal, this influence is problematic as rankings are often easily gameable by unscrupulous leaders who prey on novice copiers, and they create perverse incentives for all platform users.

著者
Daisuke Kawai
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Kyle Soska
Ramiel Capital, New York, New York, United States
Bryan Routledge
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Ariel Zetlin-Jones
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Nicolas Christin
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3613904.3642715

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Finance and Money

314
5 件の発表
2024-05-14 18:00:00
2024-05-14 19:20:00