  While pump-and-dump schemes have attracted the attention of cryptocurrency
observers and regulators alike, this paper represents the first detailed
empirical query of pump-and-dump activities in cryptocurrency markets. We
present a case study of a recent pump-and-dump event, investigate 412
pump-and-dump activities organized in Telegram channels from June 17, 2018 to
February 26, 2019, and discover patterns in crypto-markets associated with
pump-and-dump schemes. We then build a model that predicts the pump likelihood
of all coins listed in a crypto-exchange prior to a pump. The model exhibits
high precision as well as robustness, and can be used to create a simple, yet
very effective trading strategy, which we empirically demonstrate can generate
a return as high as 60% on small retail investments within a span of two and
half months. The study provides a proof of concept for strategic crypto-trading
and sheds light on the application of machine learning for crime detection.
