MyTrade Founder Fined $10K for Bot-Driven Wash Trading Across 60 Crypto Assets

The U.S. Department of Justice has secured a criminal conviction against the founder of the MyTrade platform for an automated wash-trading scheme that touched roughly 60 cryptocurrency markets. Liu Zhou pleaded guilty to conspiracy to commit market manipulation and wire fraud, and was sentenced in Boston federal court to a $10,000 fine with no prison time. The penalty is modest in dollar terms, but the case itself carries real weight: it confirms that prosecutors treat algorithmic manipulation of digital asset markets as criminal conduct, and it puts accounting firms, auditors, and CFOs on notice that pricing data from compromised markets carries audit risk they cannot ignore.

What Prosecutors Found

According to the Justice Department account reported by Decrypt, the founder deployed automated bots to execute wash trades across roughly 60 cryptocurrencies. The case grew out of an FBI undercover operation that created NexFundAI, a fictitious crypto company with a website and an Ethereum-based token, to solicit market-making services; the sting produced charges against 18 individuals and entities in October 2024. Wash trading is the practice of simultaneously buying and selling the same asset to manufacture the appearance of genuine trading activity. The bots created artificial volume figures and distorted price signals, giving outside observers a false impression of market depth and liquidity.

The Legal Basis for the Prosecution

The charges were conspiracy to commit market manipulation and wire fraud, general criminal statutes rather than crypto-specific ones. As part of the plea agreement, MyTrade MM was required to permanently deactivate its Volume Support service and to post a notice stating that volume support is a form of wash trading and illegal under the laws of the United States. Prosecutors did not need new crypto-specific legislation to bring the case; existing law was sufficient.

The $10,000 Penalty in Context

The $10,000 fine is low relative to the scale of manipulation described across 60 markets, and it was imposed with no prison time. Whatever the reason for the figure, the penalty amount does not dilute the precedent: the Justice Department has demonstrated willingness to prosecute even smaller-scale algorithmic manipulation, which signals a lower prosecution threshold than many market participants may have assumed.

Why This Matters for Accounting Firms and CFOs

Wash trading is not just a regulatory problem for the platform that hosts it. It creates downstream data integrity issues that flow directly into financial statements and tax records maintained by the counterparties whose trades were influenced by artificial prices.

Pricing Data and Fair-Value Measurement

Under ASC 820 and IFRS 13, fair value is the price that would be received in an orderly transaction between market participants. A market contaminated by wash trading is not an orderly market: the observable prices it produces do not reflect genuine supply and demand. If a firm holds a digital asset and sources its fair-value input from a venue where wash trading has occurred, the measurement may be unreliable. Auditors applying PCAOB or ISA standards are required to assess whether quoted prices represent Level 1 inputs or whether adjustments are needed, and wash-trading evidence is directly relevant to that assessment.

Cost-Basis Records and the Integrity of Historical Data

For firms that traded any of the 60 affected tokens during the period covered by the scheme, the recorded acquisition or disposal prices may have been influenced by artificial order flow. That matters for cost-basis calculations, gain and loss reporting, and the supporting schedules that underpin a tax return or audit file. Relying on crypto bookkeeping software that ingests raw exchange data without any adjustment for wash-trade-affected prices could mean that reported figures do not reflect genuine economic values.

This is not a hypothetical risk. If a token's price was artificially inflated by bot activity at the moment a client purchased it, the cost basis recorded is higher than what a genuine market would have produced. Conversely, an artificially depressed price at the point of disposal would understate a gain. Both distortions flow through to taxable income calculations and financial statement balances.

AML and Transaction Monitoring Obligations

Wash trading also has AML implications. Generating artificial volume can be a technique used to layer illicit funds, making them appear to originate from legitimate trading activity. Firms with AML obligations, including registered crypto asset service providers, broker-dealers with digital asset exposure, and any entity subject to US anti-money-laundering requirements, should consider whether the MyTrade pattern could appear in their own transaction monitoring data. A pattern of trades that net to zero economic exposure across multiple tokens is a red flag that existing rule sets may need to capture explicitly.

For broader context on how U.S. regulators are approaching sanctions and AML enforcement in the digital asset space, see our analysis of OFAC sanctions and crypto AML obligations for accounting firms and CFOs.

Practical Steps for Accounting Firms and CFOs

Review Pricing Sources for Affected Tokens

The first practical step is to identify whether any client portfolios or corporate treasury positions include tokens that were listed on MyTrade and active during the relevant period. If so, the firm should assess whether the prices used for fair-value measurement or cost-basis recording were sourced from MyTrade directly or from aggregators that weight MyTrade volume. Digital asset accounting software that allows firms to select or override pricing sources is better placed to handle this kind of review than tools that rely on a single undisclosed data feed.

Document the Assessment

Even if the conclusion is that pricing was not materially affected, that assessment should be documented in the audit or tax file. Regulators and auditors increasingly expect firms to demonstrate that they have considered the quality of crypto market data, not merely accepted it. A brief memo recording the tokens reviewed, the pricing sources consulted, and the rationale for relying on them provides meaningful protection if the matter is ever questioned.

Revisit Exchange-Level Due Diligence

This case is a prompt to formalise exchange due diligence as a standing element of the digital asset engagement process. Questions worth asking include: does the exchange publish surveillance and market integrity reports? Is it registered with or overseen by a U.S. regulator? Does it have a track record of self-reporting or cooperating with enforcement actions? Firms should build these criteria into their digital asset accounting software vendor assessments and their client onboarding checklists for engagements that involve exchange-sourced data.

The pattern of U.S. enforcement actions against crypto market manipulation is growing. For a related data point on fraud enforcement, see our coverage of the NFT founder charged with $10M fraud, which illustrates how the Justice Department is pursuing digital asset misconduct cases.

The Broader Enforcement Trajectory

The MyTrade case sits within a clear directional shift in U.S. crypto enforcement. The Justice Department has signalled that automated manipulation, including spoofing, layering, and wash trading, is a priority target regardless of the dollar size of the scheme. Its willingness to prosecute a case involving a relatively small platform and a penalty of $10,000 suggests the department is building a body of precedent rather than focusing solely on headline cases.

For accounting professionals, that trajectory has a specific implication: the question is no longer whether digital asset markets are regulated, but how thoroughly existing rules already apply. US market-conduct rules, anti-money-laundering requirements, and IRS guidance on digital assets collectively create a compliance framework that is already in force. Firms that treat crypto engagements as a compliance-light area are taking a position that the current enforcement record does not support.

Maintaining reliable records across this landscape requires digital asset accounting software that can distinguish between pricing sources, support manual overrides when market data is suspect, and produce audit-ready documentation. That is not a product recommendation; it is a description of the minimum capability a firm needs to meet its professional obligations when the underlying market data is in question.

FAQ

What is wash trading in crypto markets?

Wash trading is the practice of buying and selling the same asset simultaneously or in rapid succession with no genuine change in beneficial ownership. The purpose is to inflate reported trading volume and create misleading price signals. In the U.S., it is illegal under federal law.

How does wash trading affect financial statement figures?

If a digital asset is priced using data from a market affected by wash trading, the fair-value measurement may not represent an orderly transaction price as required under ASC 820 or IFRS 13. The recorded cost basis of assets acquired at artificially inflated or deflated prices will also be unreliable, which flows through to gain and loss calculations on disposal.

Does the MyTrade enforcement action create direct liability for firms that traded those tokens?

Not directly. The action targets the platform founder, not counterparties. However, firms that traded the affected tokens should assess whether their recorded prices were distorted, and document that assessment. Any material distortion could affect the accuracy of financial statements and tax filings, which is where professional liability arises.

What should accounting firms look for in a digital asset pricing source?

Firms should favour exchanges that publish market surveillance reports, are registered with or overseen by a recognised regulator, and have a transparent methodology for excluding self-trades and wash trades from volume and price calculations. Data aggregators that disclose their weighting methodology and allow source-level filtering provide better audit-trail support than those that do not.

Is a $10,000 criminal fine significant for a compliance programme?

The dollar amount is small, but the significance lies in the precedent, not the penalty. The case confirms that the Justice Department will prosecute algorithmic manipulation on smaller platforms using existing criminal law, without waiting for crypto-specific legislation. That lowers the threshold of conduct that firms should treat as a compliance risk when assessing the market integrity of exchanges they rely on for pricing data.

Source: Decrypt