research-article
Authors: Wen Li, Lingfeng Bao, Jiachi Chen, John Grundy, Xin Xia, Xiaohu Yang
ACM Transactions on Internet Technology, Volume 24, Issue 2
Article No.: 8, Pages 1 - 26
Published: 18 March 2024 Publication History
Metrics
Total Citations0Total Downloads571Last 12 Months571
Last 6 weeks46
New Citation Alert added!
This alert has been successfully added and will be sent to:
You will be notified whenever a record that you have chosen has been cited.
To manage your alert preferences, click on the button below.
Manage my Alerts
New Citation Alert!
Please log in to your account
Get Access
- Get Access
- References
- Media
- Tables
- Share
Abstract
The cryptocurrency market cap has experienced a great increase in recent years. However, large price fluctuations demonstrate the need for governance structures and identify whether there are market manipulations. In this article, we conduct three analyses—social media data analysis, blockchain data analysis, and price bubble analysis—to investigate whether market manipulation exists on Bitcoin, Ethereum, and Dogecoin platforms. Social media data analysis aims to find the reasons for price fluctuations. Blockchain data analysis is used to find detailed behavior of the manipulators. Price bubble analysis is used to investigate the relation between price fluctuation and manipulators’ behavior. By using the three analyses, we show that market manipulation exists on Bitcoin, Ethereum, and Dogecoin. However, market manipulation of Bitcoin is limited, and for most of Bitcoin’s price fluctuations, we found other explanations. The price for Ethereum is the most sensitive to technical updates. Technical companies/teams usually hype some new concepts (e.g., ICO, DeFi), which causes a price spike. The price of Dogecoin has a high correlation with Elon Musk’s X (formerly known as Twitter) activity, showing that influential individuals have the ability to manipulate its prices. In addition, the poor monetary liquidity of Dogecoin allows some users to manipulate its price.
References
[1]
Adebayo Adedokun. 2019. Bitcoin-Altcoin price synchronization hypothesis: Evidence from recent data. Journal of Finance and Economics 7, 4 (2019), 137–147.
[2]
C. Alexander and D. F. Heck. 2020. Price discovery in Bitcoin: The impact of unregulated markets. Journal of Financial Stability 50 (2020), 100776.
[3]
Lennart Ante. 2023. How Elon Musk’s Twitter activity moves cryptocurrency markets. Technology Forecasting and Social Change 186, A (2023), 122112.
[4]
Paul Barnes2018. Crypto currency and its susceptibility to speculative bubbles, manipulation, scams and fraud. Journal of Advanced Studies in Finance 9, 2 (18) (2018), 60–77.
[5]
Dirk G. Baur and Thomas Dimpfl. 2018. Asymmetric volatility in cryptocurrencies. Economics Letters 173 (2018), 148–151.
[6]
Walter Bazán-Palomino. 2021. How are Bitcoin forks related to Bitcoin? Finance Research Letters 40 (2021), 101723.
[7]
David M. Blei and John D. Lafferty. 2007. A correlated topic model of science. Annals of Applied Statistics 1, 1 (2007), 17–35.
[8]
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet allocation. Journal of Machine Learning Research 3 (2003), 993–1022.
Digital Library
[9]
Dmitri Boreiko and Navroop K. Sahdev. 2018. To ICO or not to ICO—Empirical analysis of initial coin offerings and token sales. SSRN. Retrieved February 5, 2024 from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3209180
[10]
Jamal Bouoiyour, Refk Selmi, Aviral Kumar Tiwari, and Olaolu Olayeni. 2016. What drives Bitcoin price. Economics Bulletin 36, 2 (2016), 843–850.
[11]
Vitalik Buterin. 2013. Ethereum White Paper. GitHub Repository.
[12]
Eng-Tuck Cheah and John Fry. 2015. Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters 130 (2015), 32–36.
[13]
Jialan Chen, Dan Lin, and Jiajing Wu. 2022. Do cryptocurrency exchanges fake trading volumes? An empirical analysis of wash trading based on data mining. Physica A: Statistical Mechanics and Its Applications 586 (2022), 126405.
[14]
Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, and Ting Chen. 2022. Defining smart contract defects on Ethereum. IEEE Transactions on Software Engineering 48, 1 (2022), 327–345.
[15]
Liang Chen, Jiaying Peng, Yang Liu, Jintang Li, Fenfang Xie, and Zibin Zheng. 2020. Phishing scams detection in Ethereum transaction network. ACM Transactions on Internet Technology 21, 1 (2020), 1–16.
Digital Library
[16]
Ting Chen, Yuxiao Zhu, Zihao Li, Jiachi Chen, Xiaoqi Li, Xiapu Luo, Xiaodong Lin, and Xiaosong Zhange. 2018. Understanding Ethereum via graph analysis. In Proceedings of the 2018 IEEE Conference on Computer Communications (INFOCOM’18). IEEE, 1484–1492.
Digital Library
[17]
Weili Chen, Jun Wu, Zibin Zheng, Chuan Chen, and Yuren Zhou. 2019. Market manipulation of Bitcoin: Evidence from mining the Mt. Gox transaction network. In Proceedings of the 2019 IEEE Conference on Computer Communications (INFOCOM’19). 964–972.
Digital Library
[18]
Weili Chen, YueJin Xu, Zibin Zheng, Yuren Zhou, Jianxun Eileen Yang, and Jing Bian. 2019. Detecting “pump & dump schemes” on cryptocurrency market using an improved apriori algorithm. In Proceedings of the 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE’19). IEEE, 293–2935.
[19]
Weili Chen, Zibin Zheng, Jiahui Cui, Edith Ngai, Peilin Zheng, and Yuren Zhou. 2018. Detecting Ponzi schemes on Ethereum: Towards healthier blockchain technology. In Proceedings of the 2018 World Wide Web Conference. 1409–1418.
Digital Library
[20]
Adrian Cheung, Eduardo Roca, and Jen-Je Su. 2015. Crypto-currency bubbles: An application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox Bitcoin prices. Applied Economics 47, 23 (2015), 2348–2358.
[21]
Usman W. Chohan. 2021. A History of Dogecoin. Discussion Series: Notes on the 21st Century. Retrieved February 5, 2024 from https://ssrn.com/abstract=3091219
[22]
Pavel Ciaian, Miroslava Rajcaniova, and d’Artis Kancs. 2018. Virtual relationships: Short- and long-run evidence from BitCoin and Altcoin markets. Journal of International Financial Markets, Institutions and Money 52 (2018), 173–195.
[23]
Shaen Corbet, Brian Lucey, and Larisa Yarovaya. 2018. Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters 26 (2018), 81–88.
[24]
Michel Cândido de Souza, Elder Tiago da Costa de Souza, and Hugo Carcanholo Iasco Pereira. 2017. Cryptocurrencies bubbles: New evidences. Empirical Economics Letters 16, 7 (2017), 739–746.
[25]
Anirudh Dhawan and Tālis J. Putniņš. 2023. A new wolf in town? Pump-and-dump manipulation in cryptocurrency markets. Review of Finance 27, 3 (2023), 935–975.
[26]
R. F. Engle and C. W. J. Granger. 1987. Co-integration and error-correction: Representation, estimation and testing. Econometrica 55, 2 (1987), 251–276.
[27]
Shuhui Fan, Shaojing Fu, Yuchuan Luo, Haoran Xu, Xuyun Zhang, and Ming Xu. 2022. Smart contract scams detection with topological data analysis on account interaction. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management. 468–477.
Digital Library
[28]
Gianni Fenu, Lodovica Marchesi, Michele Marchesi, and Roberto Tonelli. 2018. The ICO phenomenon and its relationships with Ethereum smart contract environment. In Proceedings of the 2018 International Workshop on Blockchain Oriented Software Engineering (IWBOSE’18). IEEE, 26–32.
[29]
John Fry and Eng-Tuck Cheah. 2016. Negative bubbles and shocks in cryptocurrency markets. International Review of Financial Analysis 47 (2016), 343–352.
[30]
Neil Gandal, J. T. Hamrick, Tyler Moore, and Tali Oberman. 2018. Price manipulation in the Bitcoin ecosystem. Journal of Monetary Economics 95 (2018), 86–96.
[31]
David Garcia, Claudio J. Tessone, Pavlin Mavrodiev, and Nicolas Perony. 2014. The digital traces of bubbles: Feedback cycles between socio-economic signals in the Bitcoin economy. Journal of the Royal Society Interface 11, 99 (2014), 20140623.
[32]
Adem Efe Gencer, Soumya Basu, Ittay Eyal, Robbert van Renesse, and Emin Gün Sirer. 2018. Decentralization in Bitcoin and Ethereum networks. In Proceedings of the International Conference on Financial Cryptography and Data Security. 439–457.
Digital Library
[33]
Google. 2021. Google BigQuery Introduction.Retrieved Dec 28, 2021 from https://cloud.google.com/bigquery
[34]
John M. Griffin and Amin Shams. 2020. Is Bitcoin really untethered? Journal of Finance 75, 4 (2020), 1913–1964.
[35]
Adam Hayes. 2015. What factors give cryptocurrencies their value: An empirical analysis. SSRN. Retrieved February 5, 2024 from https://ssrn.com/abstract=2579445
[36]
Adam S. Hayes. 2019. Bitcoin price and its marginal cost of production: Support for a fundamental value. Applied Economics Letters 26, 7 (2019), 554–560.
[37]
Frankenfield Jake and Overcast Kimberly. 2022. Initial Coin Offering (ICO): Coin Launch Defined, with Examples. Retrieved January 3, 2022 from https://www.investopedia.com/terms/i/initial-coin-offering-ico.asp
[38]
Josh Kamps and Bennett Kleinberg. 2018. To the moon: Defining and detecting cryptocurrency pump-and-dumps. Crime Science 7, 1 (2018), 1–18.
[39]
Ladislav Kristoufek. 2015. What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis. PLoS ONE 10, 4 (2015), e0123923.
[40]
Ladislav Kristoufek. 2019. Is the Bitcoin price dynamics economically reasonable? Evidence from fundamental laws. Physica A: Statistical Mechanics and Its Applications 536 (2019), 120873.
[41]
Ladislav Kristoufek. 2023. Will Bitcoin ever become less volatile? Finance Research Letters 51 (2023), 103353.
[42]
Jan Kubal and Ladislav Kristoufek. 2022. Exploring the relationship between Bitcoin price and network’s hashrate within endogenous system. International Review of Financial Analysis 84 (2022), 102375. DOI:
[43]
Sinan Küfeoğlu and Mahmut Özkuran. 2019. Bitcoin mining: A global review of energy and power demand. Energy Research & Social Science 58 (2019), 101273.
[44]
Nikolaos Kyriazis, Stephanos Papadamou, and Shaen Corbet. 2020. A systematic review of the bubble dynamics of cryptocurrency prices. Research in International Business and Finance 54 (2020), 101254.
[45]
Massimo La Morgia, Alessandro Mei, Francesco Sassi, and Julinda Stefa. 2020. Pump and dumps in the Bitcoin era: Real time detection of cryptocurrency market manipulations. In Proceedings of the 2020 29th International Conference on Computer Communications and Networks (ICCCN’20). IEEE, 1–9.
[46]
Massimo La Morgia, Alessandro Mei, Francesco Sassi, and Julinda Stefa. 2021. The Doge of wall street: Analysis and detection of pump and dump cryptocurrency manipulations. arXiv preprint arXiv:2105.00733 (2021).
[47]
S. F. Leroy and R. D. Porter. 1981. Stock price volatility: A test based on implied variance bounds. Econometrica 49, 3 (1981), 555–574.
[48]
Xin Li and Chong Alex Wang. 2017. The technology and economic determinants of cryptocurrency exchange rates: The case of Bitcoin. Decision Support Systems 95 (2017), 49–60. DOI:
Digital Library
[49]
Daniel Liebau and Patrick Scheuffel. 2019. Cryptocurrencies & initial coin offerings: Are they scams? An empirical study. Journal of British Blockchain Association 2, 1 (2019), 1–7.
[50]
Lukáš Pichl and Taisei Kaizoji. 2017. Volatility analysis of Bitcoin price time series. Quantitative Finance and Economics 1 (2017), 474–485.
[51]
Akash Malhotra and Mayank Maloo. 2014. Bitcoin—Is it a bubble? Evidence from unit root tests. In Proceedings of the 2014 Conference on Evidence from Unit Root Tests.
[52]
Dan McGinn, David Birch, David Akroyd, Miguel Molina-Solana, Yike Guo, and William J. Knottenbelt. 2016. Visualizing dynamic Bitcoin transaction patterns. Big Data 4, 2 (2016), 109–119.
[53]
Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, and Aram Galstyan. 2021. Identifying and analyzing cryptocurrency manipulations in social media. IEEE Transactions on Computational Social Systems 8, 3 (2021), 607–617.
[54]
Tyler Moore, Nicolas Christin, and Janos Szurdi. 2018. Revisiting the risks of Bitcoin currency exchange closure. ACM Transactions on Internet Technology 18, 4 (2018), 1–18.
Digital Library
[55]
Satoshi Nakamoto. 2008. A peer-to-peer electronic cash system. Retrieved February 5, 2024 from https://bitcoin.org/bitcoin.pdf
[56]
P. C. B Phillips, S. P. Shi, and J. Yu. 2013. Testing for Multiple Bubbles 1: Historical Episodes of Exuberance and Collapse in the S&P 500. School of Economics, Singapore Management University.
[57]
Peter C. B. Phillips, Yangru Wu, and Jun Yu. 2011. Explosive behavior in the 1990s Nasdaq: When did exuberance escalate asset values? International Economic Review 52, 1 (2011), 201–226.
[58]
Marc Pilkington. 2016. Blockchain technology: Principles and applications. In Research Handbook on Digital Transformations. Edward Elgar Publishing.
[59]
Burak Pirgaip, Burcu Dinçergök, and Şüheda Haşlak. 2019. Bitcoin market price analysis and an empirical comparison with main currencies, commodities, securities and Altcoins. In Blockchain Economics and Financial Market Innovation: Financial Innovations in the Digital Age. Springer, 141–166.
[60]
Rakesh Sharma and Amilcar Chavarria. 2022. What Is Decentralized Finance (DeFi) and How Does It Work? Retrieved January 13, 2022 from https://www.investopedia.com/decentralized-finance-defi-5113835
[61]
Raynor de Best. 2021. Cryptocurrency Market Value. Retrieved December 29, 2021 from https://www.statista.com/statistics/730876/cryptocurrency-maket-value/
[62]
Svetlana Sapuric and Angelika Kokkinaki. 2014. Bitcoin is volatile! Isn’t that right? In Business Information Workshops. Lecture Notes in Business Information Processing, Vol. 183. Springer, 255–265.
[63]
Fabian Schär. 2021. Decentralized finance: On blockchain-and smart contract-based financial markets. SSRN. Retrieved February 5, 2024 from https://ssrn.com/abstract=3571335
[64]
Yahya Shahsavari, Kaiwen Zhang, and Chamseddine Talhi. 2019. A theoretical model for fork analysis in the Bitcoin network. In Proceedings of the 2019 IEEE International Conference on Blockchain (Blockchain’19). IEEE, 237–244.
[65]
Syed Jawad Hussain Shahzad, Muhammad Anas, and Elie Bouri. 2022. Price explosiveness in cryptocurrencies and Elon Musk’s Tweets. Finance Research Letters 47, B (2022), 102695.
[66]
Yhlas Sovbetov. 2018. Factors influencing cryptocurrency prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero. Journal of Economics and Financial Analysis 2, 2 (2018), 1–27.
[67]
Donna Spencer. 2009. Card Sorting: Designing Usable Categories. Rosenfeld Media.
[68]
Marie Vasek and Tyler Moore. 2015. There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams. In Proceedings of the International Conference on Financial Cryptography and Data Security. 44–61.
[69]
Dejan Vujičić, Dijana Jagodić, and Siniša Ranđić. 2018. Blockchain technology, Bitcoin, and Ethereum: A brief overview. In Proceedings of the 2018 17th International Symposium INFOTEH-JAHORINA (INFOTEH’18). IEEE, 1–6.
[70]
Wang Chun Wei. 2018. The impact of tether grants on Bitcoin. Economics Letters 171 (2018), 19–22.
[71]
Wikipedia. 2021. Dogecoin. Retrieved December 29, 2021 from https://en.wikipedia.org/wiki/Dogecoin
[72]
Ines Wöckl. 2019. Bubble detection in financial markets—A survey of theoretical bubble models and empirical bubble detection tests. SSRN. Retrieved February 5, 2024 from https://ssrn.com/abstract=3460430
[73]
Gavin Wood. 2017. Ethereum: A Secure Decentralised Generalised Transaction Ledger. Yellow Paper. Ethereum.
[74]
Pengcheng Xia, Haoyu Wang, Bingyu Gao, Weihang Su, Zhou Yu, Xiapu Luo, Chao Zhang, Xusheng Xiao, and Guoai Xu. 2021. Trade or trick? Detecting and characterizing scam tokens on Uniswap decentralized exchange. Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, 3 (2021), 1–26.
Digital Library
[75]
Yuan Yiming, Du Hai, Shi Junjing, and Xiao Xiao. 2021. Huobi Weekly Report Analysis. Vol. 26. Retrieved Aug 17, 2018, from https://medium.com/hbus-official/big-data-weekly-26-cbc20cd979c9
[76]
Julie Young. 2021. Representative Sample. Retrieved October 29, 2021 from https://www.investopedia.com/terms/r/representative-sample.asp
[77]
Avi Mizrahi. 2017. Ethereum founder vitalik buterin: We are in an ICO bubble. Finance Magnates. https://www.financemagnates.com/cryptocurrency/news/ethereum-founder-vitalik-buterin-ico-bubble/
Index Terms
Market Manipulation of Cryptocurrencies: Evidence from Social Media and Transaction Data
Applied computing
Law, social and behavioral sciences
Economics
Information systems
Information retrieval
Retrieval tasks and goals
Information extraction
Recommendations
- Volatility Interdependence Between Cryptocurrencies, Equity, and Bond Markets
Abstract
This paper investigates (i) the return-volatility spillover between Bitcoin, Ethereum, Ripple, and Litecoin, (ii) the interdependence between cryptocurrencies’ volatility and the US equity and bond markets’ volatility, and (iii) the impact of the ...
Read More
- Stake Shift in Major Cryptocurrencies: An Empirical Study
Financial Cryptography and Data Security
Abstract
In the proof-of-stake (PoS) paradigm for maintaining decentralized, permissionless cryptocurrencies, Sybil attacks are prevented by basing the distribution of roles in the protocol execution on the stake distribution recorded in the ledger itself. ...
Read More
- Transaction fee mechanism design
Demand for blockchains such as Bitcoin and Ethereum is far larger than supply, necessitating a mechanism that selects a subset of transactions to include "on-chain" from the pool of all pending transactions. EIP-1559 is a proposal to make several ...
Read More
Comments
Information & Contributors
Information
Published In
ACM Transactions on Internet Technology Volume 24, Issue 2
May 2024
96 pages
EISSN:1557-6051
DOI:10.1145/3613553
- Editor:
- Ling Liu
Georgia Institute of Technology, USA
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [emailprotected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 18 March 2024
Online AM: 30 January 2024
Accepted: 25 January 2024
Revised: 21 November 2023
Received: 30 January 2023
Published inTOITVolume 24, Issue 2
Permissions
Request permissions for this article.
Check for updates
Author Tags
- Blockchain
- cryptocurrencies
- market manipulation
- empirical study
Qualifiers
- Research-article
Funding Sources
- National Key Research and Development Program of China
- National Science Foundation of China
- Fundamental Research Funds for the Central Universities
- ARC Laureate Fellowship
Contributors
Other Metrics
View Article Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
Total Citations
571
Total Downloads
- Downloads (Last 12 months)571
- Downloads (Last 6 weeks)46
Reflects downloads up to 25 Aug 2024
Other Metrics
View Author Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in
Full Access
Get this Article
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderFull Text
View this article in Full Text.
Full TextMedia
Figures
Other
Tables