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Crypto’s wash trading problem is ‘far more common’ than investors think, DOJ sting shows

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Crypto’s wash trading problem is ‘far more common’ than investors think, DOJ sting shows

A U.S. enforcement case against alleged crypto market manipulation is once again putting the spotlight on wash trading and the blurry line between market makers and market manipulators.

Federal prosecutors in California this week charged 10 individuals tied to firms including Gotbit, Vortex, Antier and Contrarian, accusing them of coordinating trades to inflate token prices and volumes before selling into the artificial demand. The case stemmed from an undercover FBI operation in which agents created their own token to identify firms offering manipulation services.

Defendants marketed strategies to boost trading activity that in reality amounted to pump-and-dump schemes and wash trading, leaving evidence that is far more common than expected, crypto experts Jason Fernandes from AdLunam and Stefan Muehlbauer from Certik told CoinDesk via Telegram interviews..

“Yes, despite increased enforcement, wash trading continues to be a pervasive issue, particularly among lower-cap tokens and on unregulated exchanges,” Muehlbauer said, while Fernandes stated, iIt’s far more common than most investors realize,”. They both agreed the scale remains high.

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Gotbit Founder Aleksei Andriunin, included in the recent Department of Justice indictments, pleaded guilty to two counts of wire fraud and conspiracy to commit market manipulation last year, and agreed to forfeit $23 million. U.S. prosecutors described his crimes as a “wide-ranging conspiracy” to manipulate token prices for paying clients.

Inflating volumes becomes a shortcut

The details of market manipulation exposed by the DOJ are impactful, but the underlying behavior is not.

“Wash trading exists because in crypto, liquidity is perception,” said Jason Fernandes, co-founder of AdLunam. “Volume attracts attention, listings and capital, so inflating it becomes a shortcut to relevance.”

The mechanics are straightforward: coordinated accounts trade back and forth to simulate demand, often outsourced to market makers paid to create the illusion of organic flow.

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It is far more common than investors believe or expect, particularly in long-tail tokens and on smaller exchanges where oversight is limited, Fernandes added.

“In many cases, it’s not just rogue actors. It’s projects, market-making firms and even venues themselves, all benefiting from higher reported volume.”

The DOJ said the firms included in their indictment used coordinated trading to inflate volumes and prices, ultimately selling tokens at artificially high levels to unsuspecting investors.

Recent research has repeatedly pointed to inflated activity across crypto markets. A Columbia University analysis of Polymarket found roughly 25% of historical volume showed signs of wash trading, while earlier Dune Analytics data suggested tens of billions in NFT volume on Ethereum stemmed from similar activity.

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Wash trading still a ‘pervasive issue’: Certik

“The recent actions by the U.S. Department of Justice send a clear signal,” said Stefan Muehlbauer, head of U.S. government affairs at CertiK. “The ‘wild west’ era of crypto market manipulation is facing a coordinated, global crackdown. While these indictments represent a major victory for market integrity, wash trading remains a significant concern.”

Despite years of scrutiny, the incentives behind the practice remain intact, he said. Token issuers often face pressure to meet exchange listing requirements tied to trading volume, leading some to turn to market makers to simulate activity or deploy bots that trade against themselves.

“The ‘why’ is simple: illusion of value,” Muehlbauer said. “That illusion has real consequences,” particularly because artificial volume distorts price discovery, masks weak liquidity and can funnel capital based on signals that are not real. “High volume signals to investors and exchanges that a token is hot and liquid.”

“Victims are investors relying on that liquidity and high volume data,” Fernandes said. “Wash trading distorts markets, leading to “mispriced risk and capital flowing based on signals that aren’t real.”

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Enforcement will benefit the market

The latest DOJ case stands out may bring a glimmer of hope to the industry.

“What’s notable isn’t just the charge but the method,” Fernandes said. “When the FBI is creating tokens to catch market manipulation, you’re no longer in a grey area. This is the U.S. signaling that crypto market structure is now firmly in enforcement territory.”

For market participants, the line between legitimate liquidity provision and manipulation is coming under sharper scrutiny, said the AdLunam co-founder.

Efforts to detect and reduce wash trading are improving. Regulated exchanges are deploying more sophisticated surveillance tools, while analysts are increasingly looking beyond headline volume to metrics such as order book depth, slippage and counterparty diversity.

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Enforcement may ultimately push the market forward, although for now, the DOJ case shone a light on just how pervasive wash trading continues to be, undermining trust in crypto markets.

“Crypto is moving from a loosely policed frontier market to something that has to withstand institutional scrutiny. An irony is that enforcement like this may ultimately strengthen the asset class,” Fernandes said.

In Muehlbauer’s words, “the message to the industry is clear: what was once brushed off as ‘market making’ is now being prosecuted as wire fraud and market manipulation.”

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Crypto World

DeFi Is Optimizing For gas, Not For Markets

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DeFi Is Optimizing For gas, Not For Markets

Opinion by: João Garcia, DevReal lead at Cartesi.

Decentralized finance presents itself as a transparent alternative to Wall Street. Yet, what it has largely reconstructed is a simplified version of finance, engineered less around market resilience than around the constraints of gas fees. That trade-off, once treated as a technical footnote, is increasingly shaping the limits of what DeFi can become.

So long as computational minimalism remains the overriding priority, financial robustness will remain secondary, and periods of market stress will continue to expose that imbalance.

When markets move faster than the virtual machine

DeFi has rebuilt the familiar architecture of finance, including exchanges, lending markets, derivatives and stablecoins. However, the way these systems function reveals how tightly they are bound by their execution environments.

Risk parameters tend to remain static, and although collateral thresholds can adjust, they typically do so slowly, through governance processes rather than automatic recalibration. Liquidation engines currently rely on fixed formulas rather than adaptive portfolio models that account for shifting volatility or correlations. What appears as a design preference is often a concession to computational limits.

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On Ethereum and similar chains, floating-point arithmetic is absent or emulated, iterative simulations are expensive, and continuously recomputing cross-asset exposure can quickly become impractical. The outcome is that financial logic is compressed into forms that are deterministic and affordable to execute, even if that compression strips away nuance.

This architecture performs adequately in stable conditions, but volatility has a way of testing its edges. During MakerDAO’s “Black Thursday” event in March 2020, vaults were liquidated at effectively zero bids, as auction mechanics struggled under collapsing prices and network congestion. 

In later downturns, protocols such as Aave and Compound leaned on mass liquidations triggered by fixed collateral ratios, rather than dynamic portfolio recalculations. When Curve’s pools were destabilized in 2023 following a smart contract exploit, the stress radiated outward into lending protocols that treated LP tokens as static collateral, compounding systemic risk.

In each instance, decentralization itself was not the breaking point. Rather, rigid financial logic operated inside an execution layer that could not continuously recompute risk as conditions deteriorated.

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Traditional markets evolved in the opposite direction. Banks and clearinghouses simulate thousands of stress scenarios, recalculating exposure as correlations shift and volatility regimes change. Margin requirements respond dynamically to market conditions, and the response is led by substantial computational infrastructure and mature numerical tooling. Public blockchains, by contrast, were not designed with that degree of iterative financial processing in mind.

The illusion of simplicity

Constraining computational complexity reduces certain attack surfaces. Simplicity at the protocol layer, however, does not dissolve complexity in the financial system. It merely pushes it elsewhere.

When risk cannot be modeled and recomputed transparently on-chain, it migrates off-chain into dashboards, analytics teams, discretionary parameter adjustments and emergency governance coordination. The blockchain may remain the settlement layer, but the adaptive intelligence that stabilizes the system increasingly operates outside it. During volatility spikes, protocols often depend on rapid human coordination to adjust parameters, while oracles and large token holders acquire disproportionate influence over outcomes.

The system retains its decentralized base, yet its capacity to respond flexibly depends on actors operating beyond deterministic execution. What appears structurally simple at the smart contract level can conceal a more complex and less transparent operational reality.

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DeFi did not converge on simplified finance because static ratios and deterministic curves were proven superior. It converged there because richer computational models were prohibitively expensive to run. As markets deepen, leverage increases, and instruments grow more interdependent, that compromise becomes harder to ignore. Fixed thresholds and blunt liquidation engines, initially safeguards, can begin to function as amplifiers of stress.

Computation as a missing primitive

The deeper constraint, more than decentralization, is execution design.

If verifiable execution environments begin to approximate general-purpose computing systems, the financial design space expands. Native floating-point assistance, iterative algorithms and access to established numerical libraries would allow models to be expressed directly rather than translated into simplified approximations. 

Related: Wall Street will eventually submit to the rules of DeFi

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This change would allow lending protocols to incorporate scenario-based stress testing instead of relying primarily on fixed collateral ratios. Margin requirements may also adjust in response to observed volatility rather than governance cadence. It could also see credit systems recompute multivariable risk scores transparently, replacing binary heuristics with more granular assessments.

The aim is not to introduce complexity for its own sake. It is to keep financial intelligence inside the protocol, where it remains visible and enforceable, rather than externalizing it into operational layers that users cannot easily audit. This underscores the broader point that the limitations confronting DeFi are largely architectural choices, not inevitabilities of decentralization.

A credibility ceiling

DeFi now stands at a structural crossroads. One direction preserves gas-optimized minimalism, keeping base-layer execution clean while allowing increasingly sophisticated financial logic to migrate off-chain. That path may maintain clarity at the smart contract level, but it constrains how far decentralized finance can responsibly scale.

The alternative is to treat computation itself as a first-class primitive and to accept more capable execution environments in exchange for systems that can adapt, recompute and stress-test transparently. If complex risk logic cannot live on-chain, DeFi will continue to project simplicity in code while relying on discretion in practice.

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Markets will not moderate their complexity to accommodate virtual machine constraints. If decentralized finance intends to operate at a meaningful scale, its computational foundations will have to evolve alongside the financial ambitions built on top of them.

Opinion by: João Garcia, DevReal lead at Cartesi.