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Abnormal Trading Detection in the NFT Market

Author

Listed:
  • Mingxiao Song
  • Yunsong Liu
  • Agam Shah
  • Sudheer Chava

Abstract

The Non-Fungible-Token (NFT) market has experienced explosive growth in recent years. According to DappRadar, the total transaction volume on OpenSea, the largest NFT marketplace, reached 34.7 billion dollars in February 2023. However, the NFT market is mostly unregulated and there are significant concerns about money laundering, fraud and wash trading. The lack of industry-wide regulations, and the fact that amateur traders and retail investors comprise a significant fraction of the NFT market, make this market particularly vulnerable to fraudulent activities. Therefore it is essential to investigate and highlight the relevant risks involved in NFT trading. In this paper, we attempted to uncover common fraudulent behaviors such as wash trading that could mislead other traders. Using market data, we designed quantitative features from the network, monetary, and temporal perspectives that were fed into K-means clustering unsupervised learning algorithm to sort traders into groups. Lastly, we discussed the clustering results' significance and how regulations can reduce undesired behaviors. Our work can potentially help regulators narrow down their search space for bad actors in the market as well as provide insights for amateur traders to protect themselves from unforeseen frauds.

Suggested Citation

  • Mingxiao Song & Yunsong Liu & Agam Shah & Sudheer Chava, 2023. "Abnormal Trading Detection in the NFT Market," Papers 2306.04643, arXiv.org, revised Aug 2023.
    • Handle: RePEc:arx:papers:2306.04643
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    References listed on IDEAS

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    1. Friedhelm Victor & Andrea Marie Weintraud, 2021. "Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges," Papers 2102.07001, arXiv.org.
    2. Matthieu Nadini & Laura Alessandretti & Flavio Di Giacinto & Mauro Martino & Luca Maria Aiello & Andrea Baronchelli, 2021. "Mapping the NFT revolution: market trends, trade networks and visual features," Papers 2106.00647, arXiv.org, revised Sep 2021.
    3. Pennec, Guénolé Le & Fiedler, Ingo & Ante, Lennart, 2021. "Wash trading at cryptocurrency exchanges," Finance Research Letters, Elsevier, vol. 43(C).
    4. Serneels, Sven, 2023. "Detecting wash trading for nonfungible tokens," Finance Research Letters, Elsevier, vol. 52(C).
    Full references (including those not matched with items on IDEAS)

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