Cryptocurrency Pump and Dump Schemes: Quantification and Detection

Victor, Friedhelm; Hagemann, Tanja

doi:10.1109/icdmw.2019.00045

Cited by 21 publications

(7 citation statements)

References 14 publications

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“…The increasing attention for cryptocurrencies has come with a range of manipulative activities. Several papers have studied the phenomenon of cryptocurrency pump and dump schemes [19,20,28,32] and manipulation of Bitcoin prices [16,17], both on centralized exchanges. Suspicious trader networks and manipulative transaction patterns have been identified on the Mt.…”

Section: Cryptoasset Price Manipulationmentioning

confidence: 99%

Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges

Victor

Weintraud

2021

Proceedings of the Web Conference 2021

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Cryptoassets such as cryptocurrencies and tokens are increasingly traded on decentralized exchanges. The advantage for users is that the funds are not in custody of a centralized external entity. However, these exchanges are prone to manipulative behavior. In this paper, we illustrate how wash trading activity can be identified on two of the first popular limit order book-based decentralized exchanges on the Ethereum blockchain, IDEX and EtherDelta. We identify a lower bound of accounts and trading structures that meet the legal definitions of wash trading, discovering that they are responsible for a wash trading volume in equivalent of 159 million U.S. Dollars. While self-trades and two-account structures are predominant, complex forms also occur. We quantify these activities, finding that on both exchanges, more than 30% of all traded tokens have been subject to wash trading activity. On EtherDelta, 10% of the tokens have almost exclusively been wash traded. All data is made available for future research. Our findings underpin the need for countermeasures that are applicable in decentralized systems. CCS CONCEPTS• Applied computing → Digital cash; Electronic funds transfer; Computer forensics.

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Section: Cryptoasset Price Manipulationmentioning

confidence: 99%

Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges

Victor

Weintraud

2021

Proceedings of the Web Conference 2021

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“…As others invest, the price of the cryptocurrency rises, and the organisers sell their shares at an (often) much higher price. Victor and Hagemann [46] presented a cryptocurrency pump and dump detection scheme. Quantification and detection is done based on data obtained from the Binance Exchange.…”

Section: Financial Anomaly Detectionmentioning

confidence: 99%

Synergy of Blockchain Technology and Data Mining Techniques for Anomaly Detection

2021

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Blockchain and Data Mining are not simply buzzwords, but rather concepts that are playing an important role in the modern Information Technology (IT) revolution. Blockchain has recently been popularized by the rise of cryptocurrencies, while data mining has already been present in IT for many decades. Data stored in a blockchain can also be considered to be big data, whereas data mining methods can be applied to extract knowledge hidden in the blockchain. In a nutshell, this paper presents the interplay of these two research areas. In this paper, we surveyed approaches for the data mining of blockchain data, yet show several real-world applications. Special attention was paid to anomaly detection and fraud detection, which were identified as the most prolific applications of applying data mining methods on blockchain data. The paper concludes with challenges for future investigations of this research area.

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“…Once a number of such instances has been identified, the phenomenon itself can be quantified. 17 Future work in value analytics is manifold due to the large number of assets issued in the past years, each with an individual focus and potentially distinct mechanisms. In addition to this, given that there are hundreds of cryptocurrencies with differing currency supply, the impact of currency emission, inflation, and deflation on system adoption and investor behavior can be studied.…”

Section: Value Analyticsmentioning

confidence: 99%