Competition and Product Quality: Fake Trading on Crypto Exchanges

Amiram, Dan; Lyandres, Evgeny; Rabetti, Daniel

doi:10.2139/ssrn.3745617

Cited by 15 publications

(18 citation statements)

References 48 publications

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“…Specifically, our paper provides novel empirical evidence that responds to studies questioning whether cryptocurrencies contribute to terrorist financing (e.g., Irwin and Milad [2016] and Dion-Schwarz et al [2019]). In this regard, our findings could also inform the current debate over cryptocurrency regulation (Foley et al [2019], Fusaro and Hougan [2019], Griffin and Shams [2020], Makarov and Schoar [2020], Sokolov [2021], Amiram et al [2021], and Cong et al [2022]) by demonstrating that large unregulated market institutions might unwillingly operate as facilitators of terrorism.…”

Section: Introductionsupporting

confidence: 58%

“…Second, the separation permits us to provide insights into the ongoing debate over cryptocurrency regulation (e.g., Amiram et al. [2021], Cong et al. [2022], Griffin and Shams [2020], Foley et al.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, a significant variation in the regulation of crypto exchanges coupled with flawed compliance measures suggests that terrorist funds are likely to flow mostly through unregulated exchanges. For instance, unregulated exchanges often do not observe compliance proceduressuch as KYC and AML-and are more likely to engage in deceiving activities to attract demand (Aloosh and Li [2021], Amiram, Lyandres, and Rabetti [2021], and Cong et al [2021]). 34 See the online appendix for a detailed network analysis of al Qassam wallets.…”

Section: T a B L E 2 Terrorist Attacks Sample Descriptionmentioning

confidence: 99%

“…[2019], Fusaro and Hougan [2019], Griffin and Shams [2020], Makarov and Schoar [2020], Sokolov [2021], Amiram et al. [2021], and Cong et al. [2022]) by demonstrating that large unregulated market institutions might unwillingly operate as facilitators of terrorism.…”

Section: Introductionmentioning

confidence: 99%

“…We find that users of exchanges and mixers present large positive CAVs in the weeks preceding the events. A significant variation in the quality of regulation of crypto exchanges and the level of compliance procedures, such as know-your-customer (KYC) and anti-money laundering (AML), potentially facilitates illegal activities (Amiram, Lyandres, and Rabetti [2021]). 14 As the flow of illicit funds is more likely to go through unregulated exchanges than through regulated ones, we follow Cong et al [2021] and separate these two groups according to whether they are licensed by U.S., U.K., or Japanese authorities.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Coins for Bombs: The Predictive Ability of On‐Chain Transfers for Terrorist Attacks

Amiram

Jørgensen

Rabetti

2022

J of Accounting Research

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This study examines whether we can learn from the behavior of blockchain‐based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on‐chain service providers. The mapped data set permits us to empirically conduct several analyses. First, we analyze abnormal transfer volume in the vicinity of large‐scale highly visible terrorist attacks. We document evidence consistent with heightened activity in coin wallets belonging to unregulated exchanges and mixer services—central to laundering funds between terrorist groups and operatives on the ground. Next, we use forensic accounting techniques to follow the trails of funds associated with the Sri Lanka Easter bombing. Insights from this event corroborate our findings and aid in our construction of a blockchain‐based predictive model. Finally, using machine‐learning algorithms, we demonstrate that fund trails have predictive power in out‐of‐sample analysis. Our study is informative to researchers, regulators, and market players in providing methods for detecting the flow of terrorist funds on blockchain‐based systems using accounting knowledge and techniques.

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Section: Introductionsupporting

confidence: 58%

Section: Resultsmentioning

confidence: 99%

Section: T a B L E 2 Terrorist Attacks Sample Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coins for Bombs: The Predictive Ability of On‐Chain Transfers for Terrorist Attacks

Amiram

Jørgensen

Rabetti

2022

J of Accounting Research

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Exposing Stealthy Wash Trading on Automated Market Maker Exchanges

Gan,

Wang,

Xue

et al. 2024

ACM Trans. Internet Technol.

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Decentralized Finance (DeFi), a pivotal component of the emerging Web3 landscape, is gaining popularity but remains vulnerable to market manipulations, such as wash trading. Wash trading is an illegal practice, where traders buy and sell assets to themselves within cryptocurrency exchanges to artificially inflate trading volumes and distort market perceptions. However, current research primarily focuses on traditional exchanges based on the Order-Book mechanism (similar to stock markets), while ignoring the Automated Market Maker (AMM) exchanges, which dominate over 75% of the market and represent a significant innovation within the DeFi. This study utilizes entity recognition technology to detect wash trading on AMM exchanges within Ethereum-like systems, based on the understanding that colluding addresses (perceived as the same entity) must use ETH for transaction fees and exhibit direct or indirect ETH transfer links. We identify wash trading when addresses with transfer connections almost simultaneously buy and sell assets while their total asset holdings remain nearly constant. This comprehensive blockchain network analysis, compared to focusing solely on transactions within exchanges, unveils covert wash trading activities. Our detection method achieves a 95.9% recall and a 96.7% true negative rate in identifying pools affected by wash trading, demonstrating its superiority over existing methods. Furthermore, we apply our method to 98,945 pools from Uniswap V2 & V3 (the most popular AMM exchanges on Ethereum) and identify 1,070,626 abnormal transactions, totaling $27.51 billion in trading volume. Analysis of these transactions uncovers insights into wash traders’ behaviors, including the utilization of multiple addresses and the dual roles of certain addresses as wash traders and liquidity providers. These insights are crucial for developing more effective strategies to combat fraudulent activities in the DeFi ecosystem and enhance financial scrutiny.

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Fair Value Measurement in Inactive Crypto Asset Markets

Beigman

Brennan²,

Hsieh

et al. 2023

Journal of Accounting, Auditing & Finance

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This article proposes a new dynamic method, the Principal Path Method (PPM), for pricing crypto asset against a primary or functional (fiat) currency in situations where these assets do not trade directly against the functional currency or trade at volumes that prevent resulting pricing information to qualify as Level 1 (ASC 820) for financial reporting. We base our method on the guidance provided in ASC 820, IFRS 13, and IAS 21. Our method is designed to extract prices from “compliant” markets that result in reliable inputs to the valuation process. We believe that our methodology improves the current techniques used to value thinly traded crypto assets such as using the last observable transaction price, creating a weighted-average price across multiple markets, or using data on comparable tokens, if available. Furthermore, we present empirical evidence that suggests pricing information generated by our method for non-exchangeable, thinly traded, or illiquid crypto assets better reflects the fundamental qualitative characteristics of useful information, relevance and faithful representation, and results in more reliable inputs used in the valuation process. Unlike methods currently used in practice, our method ensures the integrity of the valuation data employed by selecting prices from compliant markets.

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Competition and Product Quality: Fake Trading on Crypto Exchanges

Cited by 15 publications

References 48 publications

Coins for Bombs: The Predictive Ability of On‐Chain Transfers for Terrorist Attacks

Coins for Bombs: The Predictive Ability of On‐Chain Transfers for Terrorist Attacks

Exposing Stealthy Wash Trading on Automated Market Maker Exchanges

Fair Value Measurement in Inactive Crypto Asset Markets

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