While pump-and-dump schemes have attracted the attention of cryptocurrency observers and regulators alike, this
paper represents the first detailed empirical query of pumpand-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.