Detecting cryptocurrency pump-and-dump frauds using market and social signals

【Author】 Nghiem, Huy; Muric, Goran; Morstatter, Fred; Ferrara, Emilio

【Source】EXPERT SYSTEMS WITH APPLICATIONS

【影响因子】8.665

【Abstract】The cryptocurrency market has gained significant traction in the last decade, becoming an alternative finance platform to traditional stock market trading. Despite its rapid evolution, legal regulations have not yet caught up to the cryptocurrency market's progress, attracting the attention of scammers looking to exploit legal loopholes for profits. Pump-and-dump schemes, a well-worn fraud device, has regained relevance in this new territory. In a typical pump-and-dump scheme, scammers organize and leverage media channels to artificially inflate the price of an alternative cryptocurrency, only to quickly sell them to profit off unsuspecting buyers. The disruptive nature of pump-and-dump schemes necessitates a system to reliably forecast pump targets and the magnitude of its success. In this paper, we propose an approach to predict the target cryptocurrency for each pump before its announcement using market and social media signals using Neural Network-based architectures while offering interpretable insights into their black-box nature. Additionally, we construct models that are capable of forecasting the highest price induced by the pump after the cryptocurrency's identity is revealed within 6.1% error margin. We examine the optimal temporal windows and describe the limitations of social data to predict the manipulations in cryptocurrency trade. Our experimental results serve as proof of a feasible forecasting expert system for identifying cryptocurrency pump-and-dump frauds using publicly available data.

【Keywords】Cryptocurrency; Pump and dump; Fraud; Social media; Finance

【发表时间】2021 NOV 15

【收录时间】2022-01-01

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