Market makers are fleeing public blockchains to protect their secret trading playbooks

Markets Share Share this article Copy link X icon X (Twitter) LinkedIn Facebook Email Market makers are fleeing public blockchains to protect their secret trading playbooks Crypto trading is almost entirely public. One startup thinks it has borrowed an idea from Wall Street that could change that. By Oliver Knight | Edited by Sheldon Reback Apr 12, 2026, 2:00 p.m. Make preferred on Denis Dariotis, founder and CEO of GoQuant What to know : Close to half of all U.S. equity trading happens off public exchanges, yet virtually no equivalent exists in crypto, leaving market makers fully exposed to copy trading and public scrutiny. GoDark, starting up on Solana in May, uses zero-knowledge proofs to conceal trade details from everyone in the system, including the node operators running the order book. The platform faces the same challenges that have tripped up most DEX launches — bootstrapping liquidity and sustaining volume past the initial incentive period — with the added complication of a privacy model that regulators have not yet had to reckon with. The largest traders have a problem: how to keep their activity quiet enough to not influence market prices or reveal any long-term strategies. In traditional markets like equities, they've had that ability for decades through so-called dark pools and off-exchange venues. Even as far back as January 2025, more than half of all U.S. equities trading took place off public exchanges, according to Bloomberg data . Crypto has never had an equivalent, and the absence is increasingly difficult to ignore. Every trade on Hyperliquid, every order on a decentralized exchange, is visible to anyone paying attention, and companies like DeFiLlama and Arkham exist to collect and present that data in a digestible way. The crypto market, which prides itself on disrupting traditional finance, has replicated one of TradFi's most persistent structural problems: If you're big enough to move markets, everyone can see you coming. As a result, firms providing liquidity on public decentralized exchanges say their strategies get reverse-engineered quickly "On Hyperliquid, one of the top market makers told us they have to rotate their trading strategies every three weeks because they get copied," Denis Dariotis, co-founder of GoQuant, a crypto trading infrastructure firm backed by GSR, said in an interview. "That's the alpha problem." There are other consequences, too. Market makers — the firms providing the liquidity that keeps crypto markets functioning — operate in full public view, and the industry has developed a habit of making them the villain whenever something goes wrong. Recent scrutiny of Jane Street 's involvement in the Terra/Luna collapse is only the latest example. A large firm's onchain activity gets traced, a narrative forms and the company spends weeks managing a PR crisis over trades that, on a traditional venue, would have been entirely unremarkable. GoQuant's answer is GoDark, a decentralized exchange (DEX) set to start up on Solana in May. That platform uses zero-knowledge proofs to conceal trade details not just from other market participants, but also from the node operators running the order book. The ambition is radical: a matching engine where nobody in the system can see what they're matching. The immediate question is whether that's technically achievable at any useful speed. Zero-knowledge proofs are computationally expensive, and the architecture adds latency that privacy-agnostic systems don't have to absorb. Internal testing puts order matching at 25 to 50 milliseconds — Dariotis frames this as fast relative to most decentralized exchanges, where execution often runs into the hundreds of milliseconds, and he's right. But it's also an order of magnitude slower than what's available to firms co-located with a centralized exchange. For retail traders that gap probably doesn't matter. For the market makers GoDark is banking on to provide liquidity, it might. Which brings up the harder problem. A private exchange with no volume is just a dark room. GoDark's plan to seed liquidity mirrors what Hyperliquid did with its HLP vault — users deposit funds, the funds get deployed as market-making liquidity, participants take a cut of fees and first access to liquidations. It worked for Hyperliquid. But it has not worked for most of the DEXes that have tried to replicate the model since, which have generally seen volume collapse once the incentive period ends. Then there is the regulatory question, which the team has so far avoided having to answer directly. Traditional dark pools are private in the narrow sense that they conceal pre-trade order information, but they operate under post-trade reporting requirements and regulatory oversight. GoDark's privacy is more absolute by design, it's structurally incapable of producing a full audit trail. The inclusion of automated OFAC screening is a gesture toward compliance, but it is unlikely to satisfy regulators who have spent the past three years pushing crypto toward more transparency, not less. How that tension resolves — and whether it limits institutional participation to jurisdictions with lighter oversight — remains to be seen. GoDark is separate from GoQuant's existing institutional product of the same name, a spot DEX built with Copper and GSR that enters production next month and targets a different, narrower client base. The May launch is the retail-facing version. Market Makers Больше для вас Encryption Supremacy: Zcash and Privacy in the Age of Scale Автор CoinDesk Research 31 мар. 2026 г. Commissioned by GenZcash Most crypto privacy models weaken as blockchain data grows. Encryption-based models like Zcash strengthen. CoinDesk Research maps the five privacy approaches and examines the widening gap. Почему это важно : As blockchain adoption scales, the metadata available to machine learning models scales with it. Obfuscation-based privacy approaches are structurally degrading as a result. This report provides a comprehensive comparison of all five major crypto privacy architectures and a framework for evaluating which models remain durable as AI capabilities improve. 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