Meet the 11-person crypto startup beating Nasdaq: Physics Olympiad Jeff Yan’s Hyperliquid generates $1.24B in annual net income

Hyperliquid has pulled off something rare in financial history. An 11-person crypto derivatives exchange startup has quietly outpaced Nasdaq’s annual net income and is now shaping up to be one of the most efficient businesses on the planet. The numbers behind that claim are so far outside the norm that they’ve forced investors, traders, and analysts to revisit long-held assumptions about what a modern trading venue can look like.

The Most Efficient Business in the World Generates $113M Per Employee

DefiLlama estimates Hyperliquid’s annualized net income at $1.24 billion, which puts it ahead of Nasdaq’s $1.12 billion for the entire year of 2024. Nasdaq employs more than 9,000 people. Hyperliquid has 11. That comes out to an astonishing $113 million in net income per employee, a figure that instantly places Hyperliquid at the top of global finance in terms of operational efficiency.

The platform’s volume numbers tell the same story. Hyperliquid processed $420.3 billion in trading volume during August, marking its strongest month yet and extending its edge over Robinhood for the fourth straight month. Robinhood reported $227.5 billion for August across all product lines—including equities, options, and crypto—while Hyperliquid logged $398 billion in perpetual futures and another $22.3 billion in spot trading. It has now beaten Robinhood every month since May, and the gap keeps widening.

Hyperliquid’s growth has pushed its HYPE token up roughly 760% since launch, hitting a record high of $57.30. The platform is now clearing more than $10 billion in daily volume, a figure that places it in the upper tier of global trading venues, both centralized and decentralized.

But the real story isn’t the revenue or the volume. It’s the founder.

Who Is Jeff Yan? Inside the Founder Behind Hyperliquid’s Breakout

Jeff Yan’s profile reads like a checklist for someone destined to build something unusual. He graduated from Harvard with degrees in computer science and mathematics, competed at the highest levels as an International Physics Olympiad gold and silver medalist, and began his career as a quant at Hudson River Trading, one of the most sophisticated high-frequency trading firms on the planet.

Jeff moved from HFT into crypto long before it was fashionable. In 2018, fascinated by smart contracts, he left HRT to explore how automated markets might evolve. He tried building an L2 exchange protocol in San Francisco—an idea that stalled, but not for lack of potential. He stepped away from the exchange concept and returned to trading, where he spotted inefficiencies so large that “you could write simple Python code and potentially retire.”

Jeff Yan’s profile (Credit: LinkedIn)

Coming from equities, Jeff was stunned at how loose crypto markets were. Many exchanges had quirks that created opportunities for careful traders but headaches for anyone trying to operate at scale. He would later describe this period as a crash course in how fragile trading infrastructure can be. Weak routers, poor matching engines, and unpredictable behavior across centralized exchanges created an environment where staying profitable required constant adaptation.

One of the biggest surprises came from Jeff’s own high-frequency P&L. He noticed that his P&L moved in the opposite direction of medium-term price moves across the market. That pattern led him to rethink how volatility, liquidity, and flow interact. He began paying closer attention to execution paths, informed traders, toxic flow conditions, and the impact of adversarial bots that targeted market makers.

These lessons shaped Hyperliquid.

Jeff saw that decentralized exchanges were struggling with issues that would never pass inside traditional HFT environments—latency swings, poor order-book performance, inconsistent liquidity, and a lack of reliable execution during moments of stress. If centralized exchanges had their quirks, decentralized ones often had outright limitations.

Hyperliquid came from a simple question he kept returning to: What if you built a decentralized trading venue with the performance characteristics expected by serious traders?

That single idea has now reshaped the entire project.

Jeff’s long-term mission can be summed up in a line he repeats often: “Creating an AWS for liquidity.” Not a lightweight DEX experiment. Not a weekend DeFi project. A full-stack trading environment built from the ground up with its own chain, tuned for throughput, stability, and predictable execution.

Hyperliquid’s numbers show how far that idea has already gone.

Hyperliquid’s Volume Surge and the Robinhood Comparison

The streak started in May, when Hyperliquid posted $256 billion in volume compared with Robinhood’s $192 billion. In June, the margin grew again, to $231 billion from $193 billion. July widened the gap even further at $330.8 billion vs. $237.8 billion, a 39% lead.

August blew past all of them.

Hyperliquid crossed $420.3 billion in monthly volume for the first time, a nearly 85% edge over Robinhood’s August figures. The consistency of the trend suggests that this isn’t luck or a momentary spike in trader appetite. Hyperliquid’s order-book system, its speed, and its execution conditions appear to be bringing in capital at a pace other decentralized exchanges haven’t matched.

This shift supports something Jeff has studied for years: liquidity flows toward venues that behave predictably under pressure. Reliability attracts size. Size attracts more size. And eventually, that creates a moat.

Why Hyperliquid’s Profit Metrics Matter

Net income per employee is one of the clearest signals in business. It measures whether an organization is productive or bloated. Nasdaq’s ratio sits at roughly $123,000 per employee. Hyperliquid sits at $113 million per employee.

That’s a 915x difference.

The gap isn’t about labor costs or headcount efficiency alone. It hints at something much deeper: the business’s structure. Hyperliquid was built from the ground up to minimize operational drag, limit bureaucracy, reduce overhead, and automate everything that can be automated. The platform’s structure enables it to generate margins that traditional financial institutions can’t achieve without drastic changes.

This is why Hyperliquid continues to draw the attention of traders, analysts, and founders. It’s proving that a small group with strong engineering, clear focus, and uncompromised infrastructure can outperform institutions with thousands of employees, decades of history, and broad regulatory clearance.

A New Model for Trading Infrastructure

Hyperliquid isn’t replacing centralized exchanges anytime soon, but it’s forcing a conversation about what a trading venue needs to look like in the next decade. Jeff’s focus on reliability, throughput, and execution quality mirrors lessons he learned from HRT, where any micro-failure in infrastructure could collapse an entire strategy.

He’s now applying those lessons to a public chain.

The bet is simple: traders care about fill quality, uptime, speed, and liquidity conditions. If you deliver those four consistently, capital will find you—no matter where you’re based or how big your team is.

For Hyperliquid, that bet is already paying out in the form of record volume, rising token performance, and a financial profile that looks nothing like a startup with eleven people.

The question is: where does this go next? For now, Hyperliquid has done something few thought possible: prove that a small team can run one of the most profitable trading venues in global markets—and beat Nasdaq in the process.

Here’s a deeper look at Jeff Yan’s background, his approach to high-frequency trading, and the ideas that shaped Hyperliquid’s architecture.