The Doge of Wall Street: Analysis and Detection of Pump and Dump Cryptocurrency Manipulations

Abstract

Cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these assets, and nowadays, cryptocurrency exchanges process transactions for over 100 billion US dollars per month. Despite this, many cryptocurrencies have low liquidity and are highly prone to market manipulation. This paper performs an in-depth analysis of two market manipulations organized by communities over the Internet: The pump and dump and the crowd pump. The pump and dump scheme is a fraud as old as the stock market. Now, it got new vitality in the loosely regulated market of cryptocurrencies. Groups of highly coordinated people systematically arrange this scam, usually on Telegram and Discord. We monitored these groups for more than 3 years detecting around 900 individual events. We report on three case studies related to pump and dump groups. We leverage our unique dataset of the verified pump and dumps to build a machine learning model able to detect a pump and dump in 25 seconds from the moment it starts, achieving the results of 94.5% of F1-score. Then, we move on to the crowd pump, a new phenomenon that hit the news in the first months of 2021, when a Reddit community inflates the price of the GameStop stocks (GME) by over 1,900% on Wall Street, the world’s largest stock exchange. Later, other Reddit communities replicate the operation on the cryptocurrency markets. The targets were DogeCoin (DOGE) and Ripple (XRP). We reconstruct how these operations developed and discuss differences and analogies with the standard pump and dump. We believe this study helps understand a widespread phenomenon affecting cryptocurrency markets. The detection algorithms we develop effectively detect these events in real-time and help investors stay out of the market when these frauds are in action.

Self-induced consensus of Reddit users to characterise the GameStop short squeeze

“…An inherent limitation of our empirical analyses is that we have focused on a single unprecedented financial mass action. Although we have briefly shown some similar case studies as well as counterexamples, a more indepth analysis of several (possibly future) events of the same type can help corroborate or falsify our findings 17 . Another empirical limitation is that we have derived the users interaction network from Reddit conversation data, while part of the coordination of the GME operation happened on other platforms as well, like Discord.…”

Forecasting cryptocurrency's buy signal with a bagged tree learning approach to enhance purchase decisions

“…La Morgia et al ( 2023 ) used Random Forest and AdaBoost to build a machine-learning model to detect pump and dump instances in the DogeCoin and Ripple markets, analyzing many such events to highlight the dangers of market manipulation. Hu et al ( 2023 ), a neural network model known as a sequence-based neural network (SNN) was introduced to predict the likelihood of pump-and-dump behavior in Bitcoin trading.…”

Characterizing Information Propagation in Fringe Communities on Telegram

“…Another issue regarding these platforms, in particular Telegram and Discord, is that they are also commonly used for the practice of diverse forms of digital scams (La Morgia et al 2021). Especially, a vast range of cryptocurrency schemes to steal digital activities from users to pump-anddump manipulation (Hamrick et al 2021;Andryukhin 2019;Morgia et al 2022;Gao et al 2021;Nizzoli et al 2020;Mirtaheri et al 2021). The architecture of these messaging platforms facilitates such abuses by providing a private, secure, and anonymous environment for cybercriminals to interact with their customers in underground markets (Hou, Wang, and Wang 2022).…”