IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v15y2023i8p267-d1214902.html
   My bibliography  Save this article

A Survey on Pump and Dump Detection in the Cryptocurrency Market Using Machine Learning

Author

Listed:
  • Mohammad Javad Rajaei

    (Department of Electrical, Computer, and Software Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, Canada)

  • Qusay H. Mahmoud

    (Department of Electrical, Computer, and Software Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, Canada)

Abstract

The popularity of cryptocurrencies has skyrocketed in recent years, with blockchain technologies enabling the development of new digital assets. However, along with their advantages, such as lower transaction costs, increased security, and transactional transparency, cryptocurrencies have also become susceptible to various forms of market manipulation. The pump and dump (P&D) scheme is of significant concern among these manipulation tactics. Despite the growing awareness of P&D activities in cryptocurrency markets, a comprehensive survey is needed to explore the detection methods. This paper aims to fill this gap by reviewing the literature on P&D detection in the cryptocurrency world. This survey provides valuable insights into detecting and classifying P&D schemes in the cryptocurrency market by analyzing the selected studies, including their definitions and the taxonomies of P&D schemes, the methodologies employed, their strengths and weaknesses, and the proposed solutions. Presented here are insights that can guide future research in this field and offer practical approaches to combating P&D manipulations in cryptocurrency trading.

Suggested Citation

  • Mohammad Javad Rajaei & Qusay H. Mahmoud, 2023. "A Survey on Pump and Dump Detection in the Cryptocurrency Market Using Machine Learning," Future Internet, MDPI, vol. 15(8), pages 1-17, August.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:8:p:267-:d:1214902
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/15/8/267/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/15/8/267/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sihao Hu & Zhen Zhang & Shengliang Lu & Bingsheng He & Zhao Li, 2022. "Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump," Papers 2204.12929, arXiv.org, revised Apr 2023.
    2. Álvaro Cartea & Sebastian Jaimungal & Yixuan Wang, 2020. "Spoofing and Price Manipulation in Order-Driven Markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 27(1-2), pages 67-98, July.
    3. Marwa Alyami & Reem Alhotaylah & Sawsan Alshehri & Abdullah Alghamdi, 2023. "Phishing Attacks on Cryptocurrency Investors in the Arab States of the Gulf," JRFM, MDPI, vol. 16(5), pages 1-14, May.
    4. Nurullah Celal Uslu & Fuat Akal, 2022. "A Machine Learning Approach to Detection of Trade-Based Manipulations in Borsa Istanbul," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 25-45, June.
    5. Friedhelm Victor & Andrea Marie Weintraud, 2021. "Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges," Papers 2102.07001, arXiv.org.
    6. Jiahua Xu & Benjamin Livshits, 2018. "The Anatomy of a Cryptocurrency Pump-and-Dump Scheme," Papers 1811.10109, arXiv.org, revised Aug 2019.
    7. Massimo La Morgia & Alessandro Mei & Francesco Sassi & Julinda Stefa, 2020. "Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations," Papers 2005.06610, arXiv.org, revised Sep 2024.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dun Li & Dezhi Han & Zibin Zheng & Tien-Hsiung Weng & Kuan-Ching Li & Ming Li & Shaokang Cai, 2024. "Does Short-and-Distort Scheme Really Exist? A Bitcoin Futures Audit Scheme through BIRCH & BPNN Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1649-1671, April.
    2. Sihao Hu & Zhen Zhang & Shengliang Lu & Bingsheng He & Zhao Li, 2022. "Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump," Papers 2204.12929, arXiv.org, revised Apr 2023.
    3. Dean Fantazzini & Yufeng Xiao, 2023. "Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases," Econometrics, MDPI, vol. 11(3), pages 1-73, August.
    4. Kaihua Qin & Liyi Zhou & Yaroslav Afonin & Ludovico Lazzaretti & Arthur Gervais, 2021. "CeFi vs. DeFi -- Comparing Centralized to Decentralized Finance," Papers 2106.08157, arXiv.org, revised Jun 2021.
    5. David Ardia & Keven Bluteau, 2023. "The Role of Twitter in Cryptocurrency Pump-and-Dumps," Papers 2306.02148, arXiv.org.
    6. Gandal, Neil & Hamrick, JT & Rouhi, Farhang & Mukherjee, Arghya & Feder, Amir & Moore, Tyler & Vasek, Marie, 2018. "The Economics of Cryptocurrency Pump and Dump Schemes," CEPR Discussion Papers 13404, C.E.P.R. Discussion Papers.
    7. Xihan Xiong & Zhipeng Wang & Tianxiang Cui & William Knottenbelt & Michael Huth, 2023. "Market Misconduct in Decentralized Finance (DeFi): Analysis, Regulatory Challenges and Policy Implications," Papers 2311.17715, arXiv.org, revised Mar 2024.
    8. Andrea Barbon & Angelo Ranaldo, 2023. "NFT Bubbles," Swiss Finance Institute Research Paper Series 23-20, Swiss Finance Institute.
    9. Alvaro Arroyo & Alvaro Cartea & Fernando Moreno-Pino & Stefan Zohren, 2023. "Deep Attentive Survival Analysis in Limit Order Books: Estimating Fill Probabilities with Convolutional-Transformers," Papers 2306.05479, arXiv.org.
    10. Niklas Konstantin Klein & Fritz Lattermann & Dirk Schiereck, 2023. "Investment in non-fungible tokens (NFTs): the return of Ethereum secondary market NFT sales," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 241-254, July.
    11. Taro Tsuchiya, 2021. "Profitability of cryptocurrency Pump and Dump schemes," Digital Finance, Springer, vol. 3(2), pages 149-167, June.
    12. Costola, Michele & Iacopini, Matteo & Santagiustina, Carlo R.M.A., 2021. "On the “mementum” of meme stocks," Economics Letters, Elsevier, vol. 207(C).
    13. Mingxiao Song & Yunsong Liu & Agam Shah & Sudheer Chava, 2023. "Abnormal Trading Detection in the NFT Market," Papers 2306.04643, arXiv.org, revised Aug 2023.
    14. Davide Debortoli & Mario Forni & Luca Gambetti & Luca Sala, 2020. "Asymmetric monetary policy tradeoffs," Economics Working Papers 1742, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2023.
    15. Daniel Kirste & Niclas Kannengie{ss}er & Ricky Lamberty & Ali Sunyaev, 2023. "How Automated Market Makers Approach the Thin Market Problem in Cryptoeconomic Systems," Papers 2309.12818, arXiv.org, revised Sep 2023.
    16. Peter Fratrič & Giovanni Sileno & Sander Klous & Tom Engers, 2022. "Manipulation of the Bitcoin market: an agent-based study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    17. Chen, Jialan & Lin, Dan & Wu, Jiajing, 2022. "Do cryptocurrency exchanges fake trading volumes? An empirical analysis of wash trading based on data mining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    18. Vincent Gramlich & Tobias Guggenberger & Marc Principato & Benjamin Schellinger & Nils Urbach, 2023. "A multivocal literature review of decentralized finance: Current knowledge and future research avenues," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-37, December.
    19. Haochen Li & Maria Polukarova & Carmine Ventre, 2023. "Detecting Financial Market Manipulation with Statistical Physics Tools," Papers 2308.08683, arXiv.org.
    20. Arthur A. B. Pessa & Matjaz Perc & Haroldo V. Ribeiro, 2023. "Age and market capitalization drive large price variations of cryptocurrencies," Papers 2302.12319, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:15:y:2023:i:8:p:267-:d:1214902. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.