PodcastOdd LotsJeff Yan

Jeff Yan's Plan to Bring the Entire Financial Industry Onto Hyperliquid

Jeff Yan presents Hyperliquid as a neutral, on-chain infrastructure layer that could support a broad range of financial markets, while emphasizing that hosting even 90% of finance remains an aspirational goal. He describes how validators, consensus, order-book clearing, and on-chain data could affect resilience, market deployment, and oversight, while noting the system's technical and resource constraints. The hosts and Yan also discuss derivatives, perpetuals, IPO access, and the role of oracles in pricing and convergence.

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Key Takeaways

Jeff Yan says the administration and CFTC favor incorporating on-chain financial infrastructure into the existing system rather than taking an extremely restrictive approach. He envisions regulation applying at the deployer layer, while suggesting regulators may value verifiable on-chain balance checks over processes that rely on trust and disclosure.

Yan describes Hyperliquid as an ambitious neutral layer for finance, with hosting even 90% of finance framed as a distant aspiration. Its permissionless validators work toward a shared network state under a two-thirds non-Byzantine stake assumption; the active network uses the 27 highest-staked validators from a set of 30-something, and running a node currently requires 128 GB of RAM.

Yan presents Hyperliquid’s order-book clearing, global distribution, and liquidity concentration as reusable tools for different market types, not as an effort to replace traditional operators. He argues that institutions could adopt new technology while retaining their customer relationships, trusted brands, and services, and that distributed-validator rails could let an exchange continue progressing when one or more validators go down.

Under HIP-3, a deployer can list a market by specifying its terms, while setting the oracle, leverage limits, and settlement terms; users therefore rely on the deployer to publish a representative oracle price. Deployment functionality currently requires 500,000 HYPE, and slots are allocated through a Dutch auction because each market consumes network computing resources that remain limiting even though they may become less scarce as the network scales.

Yan says perpetual contracts typically track an index through an oracle reporting an off-chain value, but if spot markets move onto Hyperliquid, the oracle could instead use on-chain information. He also says the system clamps consecutive oracle updates to a 1% relative change to help process price changes and leveraged positions orderly, while funding payments can promote perpetual-price convergence—potentially more slowly when funding is lower.

GEO-POLITICS

On-Chain Policy — Jeff Yan says the current administration and CFTC favor a proactive approach to on-chain financial infrastructure. He argues the United States should find ways to incorporate the technology into the existing financial system rather than take an extremely restrictive stance.

“But the CFTC, I think the current administration wants to kind of take a proactive approach towards on chain rails for finance…”—

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TECHNOLOGY

Financial Ambition — Jeff Yan describes Hyperliquid as a neutral layer intended to support finance broadly and improve on fragmented electronic markets. Hosting even 90% of finance would be a major success, he says, but that goal is aspirational and still a long way off.

“But the short of it is a neutral layer on which finance can ultimately happen…”—

Global State — Jeff Yan describes Hyperliquid as a neutral blockchain run by permissionless validators that can reach a consistent view of network state. This relies on the assumption that two-thirds of network stake is non-Byzantine; achieving a single global state required work at the consensus layer.

“There's the protocol. It's it's a neutral blockchain…”—

Exchange Resilience — Jeff Yan argues that a regulated exchange could benefit from an on-chain network's resilience. With distributed validators, one or more can go down while the network continues agreeing on state and making progress, reducing reliance on any single component of the exchange technology stack.

“If the rails on which it are…”—

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ECONOMY

Deployer Regulation — Jeff Yan says he can envision regulation applying to deployers rather than the protocol itself. He compares the protocol to TCP/IP: it can support financial stacks without being regulated, while regulation applies where controls are exercised.

“I can very much see that world. I think that's that's an astute way to kind of frame it. I think that's a…”—

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MARKETS

Layered Products — The hosts describe markets as adding instruments on top of underlying assets, including tokenized stocks, crypto tokens in ETFs, derivatives, and prediction markets. One host says derivatives have been a bigger market than the underlying for a while; a prediction market on SK Hynix's next-ten-minute close is offered as an example that may or may not exist.

“Essentially, I kind of think like we're in this moment where so many different instruments can be expressed as other instruments in various ways…”—

On-Chain Liquidations — Jeff Yan says liquidation thresholds and execution are rules-based properties of the clearing system, not prices set subjectively by an individual. On Hyperliquid, both the clearing system and liquidation mechanism are implemented on-chain.

“The liquidation is set by the system. Mhmm. So it's not a it's not a subjective. It's not like someone actively setting a liquidation price system. It's rules based. Property…”—

Deployment Auctions — Jeff Yan says deployers currently stake 500,000 HYPE to unlock deployment functionality. Slots are allocated through a Dutch auction because each market's order book and clearing system use network computing resources. Those resources may become less scarce as the network scales, but remain limiting. The auction price falls over time; the first bidder wins, and the price resets to twice the last clearing price.

“Yeah, they have to stake 500,000 currently…”—

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Hyperliquid’s Finance Ambition

The hosts introduce Hyperliquid as a growing venue for new financial instruments, and Yan describes it as a neutral on-chain layer intended to support finance.

Validators And Resilient Markets

Yan explains how validators reach consensus and argues that distributed on-chain infrastructure can make markets more resilient without excluding regulated market operators.

Perpetuals And On-Chain Clearing

Yan describes counterparties, collateral, rule-based liquidations, and how Hyperliquid’s on-chain clearing system carries out the mechanics of perpetual contracts.

Deployers, Oracles, And Auctions

Yan explains how deployers use staked tokens and oracle publishers to launch markets, while Dutch auctions allocate scarce deployment capacity.

Market Access And IPOs

Yan argues that permissionless market deployment can broaden access to financial opportunities, while noting that derivatives do not provide the ownership cash flows of shares.

Building Hyperliquid’s Network

Yan recounts leaving high-frequency trading to build an on-chain perpetuals venue, then explains why the project required new network infrastructure rather than simply another exchange.

Oracle Risks And Price Discovery

Yan discusses oracle errors, argues that derivative volume need not be capped by underlying-market volume, and explains protocol safeguards and how funding can help prices converge.

Institutions And Regulation

Yan sees traditional institutions as potential adopters rather than targets for displacement, and argues that regulation can focus on deployers exercising market controls.

U.S. Access And On-Chain Oversight

Yan cautions U.S. users against violating platform terms and says transparent, verifiable balance data may help regulators assess on-chain financial infrastructure.

Perpetuals And Deployment Strategy

The hosts close by recommending listeners understand perpetuals, noting Hyperliquid’s distinctive deployment rules, and discussing the strategy and game theory behind launching markets.

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Important Disclaimers

Not Investment Advice: For education only — not financial, tax or legal advice.

AI-Generated: Made by AI from source transcripts and may contain errors.

No Guarantees: Past performance does not predict future results; investing carries risk.

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