Trade[XYZ] has established 92 markets and captured 98% of HIP-3 volume on Hyperliquid in 8 months

Author: Mohit Pandit

Compiled by Deep潮 TechFlow

DeepInsight Summary: Trade[XYZ] has achieved 98% of HIP-3 trading volume on Hyperliquid, raising concerns that it might take over. However, data shows that Trade[XYZ] built an institutional-grade stock perpetuals market in just eight months, bringing 300,000 users to Hyperliquid, with 97% of trading occurring on Hyperliquid’s frontend, and both parties splitting fees equally—this is not a threat, but a successful validation of Hyperliquid’s strategy: open infrastructure, letting professional teams compete, and letting liquidity determine the winners.

(Data as of June 2026) With every increase in HIP-3 holdings, every basis point rise in trading volume share, every new pre-IPO asset listing, and every tweet about Hyperliquid leading price discovery for the world’s largest and most watched assets, the voice in everyone’s mind grows louder.

Is Trade[XYZ] a threat to Hyperliquid’s survival? Has Hyperliquid handed over the kingdom’s keys? If Trade[XYZ] launches a token, will HYPE be doomed?

I plan to use data and first-principles reasoning to demonstrate why I believe Trade[XYZ] adds value to Hyperliquid, and consequently to HYPE.

The conventional argument is narrow: Trade[XYZ] locks in HYPE, lists and operates a new market, generates trading fees, and recycles those fees into HYPE buybacks. These points are valid, but in my view, they underestimate the relationship between Hyperliquid and the deployer—in this case, @tradexyz. The reality is that Trade[XYZ] spent eight months building the most difficult product in this category: a truly liquid market for stock, index, commodity, and forex perpetuals. It has demonstrated that HIP-3 can support non-crypto perpetuals with professional, institutional-grade liquidity, while Hyperliquid retains users, matching engine activity, fee sharing, auction demand, and ecosystem narrative—without bearing direct responsibility for listing or regulation.

The vertical path involves building all markets yourself, acquiring assets, operating oracles, recruiting market makers, assuming risk, and capturing all the profits; Lighter and Ostium (pure RWA) are vertically integrated products. The horizontal path provides the underlying infrastructure, allowing permissionless deployers to build markets on top and share fee revenue; this is Hyperliquid’s HIP-3, with @tradexyz being one such deployer. However, interpreting HIP-3 as merely horizontal for the sake of being horizontal is incorrect. The correct understanding is: this is an application for access.

Hyperliquid believes that the enduring advantages of on-chain finance lie in the core infrastructure—L1, clearinghouse, and matching engine—and the core team has devoted nearly all its efforts to these components. The bet is that the best operators will choose to build on this infrastructure, and to attract the best operators, it must continuously evolve toward higher performance and neutrality. There is only one CME, one NYSE, one Hong Kong Exchange in the world. Liquidity attracts liquidity; a category without a single dominant liquidity winner has already lost. Hyperliquid’s ambition is to become the home for all finance—a neutral foundation upon which winners in every category can build. HIP-3 is the mechanism to achieve this. It does not crown winners; it opens a track for the best operators to compete in building the deepest markets, letting liquidity itself decide. The ultimate winner brings immense value back to Hyperliquid: fees, buybacks, and users—while retaining its true rewards. From this perspective, centralization is not a failure of the model; it is the model functioning exactly as finance has always operated.

However, this model has faced many objections, and I believe we should fairly consider them.

The first is Hyperliquid giving up future value by allowing deployers to retain about half of the fees and hold the franchise, thereby forfeiting revenue it could have captured by building its own stock perpetuals. The second is more pointed: HIP-3 is disguised vertical integration. One deployer accounted for approximately 98% of HIP-3 trading volume, sparking allegations of favoritism (often pointing to connections between Trade[XYZ] and the Unit ecosystem), while Hyperliquid still takes 50% of the fees.

In my view, this greatly underestimates the difficulty of building an institutional-grade real-world asset market. The sole purpose of this report is to present a data-driven, first-principles analysis: whether this current model has even a remote chance of success.

“It’s just a matter of listing the asset” is the most common misconception about this business. Listing is the easy part; the real challenge and competitive advantage lie in enabling newly listed markets to handle large trading volumes. Trade[XYZ]’s data highlights three clear challenges: 1. Listing quickly enough to capture demand, 2. Attracting market makers who can create depth, and 3. Maintaining liquidity that is economically viable and sustainably operational for these markets.

Perpetual contracts markets only have value if they exist when traders think of them. From precise on-chain registration to the first trade, the median time to launch for Trade[XYZ] is just 3.3 days, with 65% of markets launching within a week and 47% within three days.

The depth of [XYZ] trading is both deep and well-distributed. Leading index and commodity markets feature institutional-grade order depth: XYZ100 has $2.6 million in orders within 10 basis points of the mid-price, the S&P 500 has $964,000, and gold has $759,000, while individual stocks like NVIDIA and Tesla also offer sufficient trading volume for comfortable execution. In contrast, median markets typically have only around $20,000 in orders within 10 basis points. This is how rational market makers allocate capital.

The real skill lies in acquiring market makers, as their presence tightens the market. Among 73 markets with sufficient data, the correlation between the number of daily unique market maker wallets and bid-ask spreads is -0.72, between trading volume and spreads is -0.82, and between trading volume and open interest is +0.96. The volume-weighted average bid-ask spread across all books is 2.33 basis points, with daily turnover approximately 2.9 times the open interest. Trade[XYZ]’s advantage lies in its ability to secure the business development and capital efforts of market makers—work that generates tight, deep markets.

It’s worth asking from first principles: why is acquiring this liquidity so difficult, and why has only one deployer successfully scaled these markets? Market makers profit from the spread, but they can only survive by managing what remains on their books after each trade. Simply put, market makers need hedging strategies. The primary risk is pure inventory risk: every trade pushes the trading desk long or short, and an unhedged trend is a major red flag. For equities, hedging is critical. While crypto perpetuals can be hedged around the clock on another crypto exchange, the only true hedges for equity perpetuals are the underlying stocks, ETFs, or futures—which trade only during regular market hours. During regular trading hours, a desk can hedge its TSLA perpetual inventory with TSLA shares, capturing the spread with near-zero risk, allowing it to quote tight and deep prices. But once the market closes, it holds naked inventory; the rational response is to widen the spread, reduce depth, or stop quoting altogether. Before an IPO, there is simply no hedging available—that’s why those books are thin leading up to listing. Additionally, there is adverse selection (a larger share of after-hours flow consists of informed traders), funding rates and holding costs (funding rates must anchor the perpetual to the index without making hedging uneconomical), and oracle or gap risk (perpetuals settle against an oracle; stale, manipulable, or gapped mark prices create uncontrollable liquidation risk, making it impossible to market-make at scale).

Discovery Bounds constrain the mark price to within ±1x the maximum reference leverage (approximately 5% for 20x leverage), re-anchoring it in discrete, market-capped steps to establish a hard upper limit until external pricing recovers. Combined with liquidation protection, this prevents positions from being liquidated when the liquidation price falls outside the active bounds. In simple terms, there is a known upper limit to how far price can move in a single step; within this limit, the exchange will not liquidate trading positions, ensuring that the worst-case scenario for unhedged overnight inventory is bounded and quantifiable, rather than open-ended. Additionally, per-market funding rate multipliers scale the standard funding rate by 0.5 (approximately a 5.5% annual baseline), but reduce it to 0.005 for pre-IPO assets. Funding rates tether perpetual contracts to fair value without overburdening market makers; for pre-IPO assets with no underlying stock for arbitrage, the rate is nearly fully shut off, so holding positions is not inherently unprofitable. Together, these mechanisms form a toolkit for enabling markets that, by first principles, cannot be market-made once hedging disappears.

Measure the order book depth of the top ten stocks across different time periods; overnight depth remains at approximately 116% of spot session levels. Single stocks like NVIDIA and Tesla have actually seen increased depth, as perpetual contracts become the only active price source after spot markets close, concentrating quotes there. On weekends, when even index futures are closed and hedging disappears entirely for two days, depth shrinks to about 37%. It should be honestly acknowledged that this boundary gives Trade[XYZ]’s after-hours book resilience, but not magically superior performance. The enduring differentiators remain its daytime depth, order flow, and the genuine breadth of markets that are difficult to market-make. The data supports that Trade[XYZ]’s risk mechanisms enable market makers to maintain overnight depth—something first-principles predictions would suggest should collapse—which itself is a non-trivial engineering feat that makes these markets marketable.

Trade[XYZ] doesn’t just go live and disappear. Within the last approximately 300 on-chain operation windows, it executed 294 distinct risk management actions: 54 position limit adjustments, 35 growth mode switches, 34 funding rate multipliers adjustments, 28 trading pauses, and 11 margin mode changes—plus asset-specific annotations. This represents continuous, market-driven risk management across 92 underlying assets, handling real trading sessions, pauses, and funding rates—it’s a full-time market operations business.

Difficulty is best understood through comparison. Solana’s tokenized spot stocks (xStocks) represent over $25 billion in total trading volume, but actual DEX trading volume is only around $517 million. Ostium, a dedicated, funded RWA perpetuals DEX, has accumulated approximately $59 billion in trading volume, yet its open interest is only about $115 million—just 1/24th of Trade[XYZ]. Newer entrants like Variational don’t even attempt to build native depth; instead, they aggregate liquidity via RFQ from Hyperliquid, Lighter, and centralized exchanges, routing orders to Hyperliquid for the liquidity in question. The clear leader in the on-chain stock perpetuals category—far ahead of the rest—is Trade[XYZ] on Hyperliquid.

The natural assumption is that the deployer owns the users through their own frontend. The truth is exactly the opposite. Measuring the frontend code responsible for generating each trade marker on the taker side reveals that approximately 97% of the trading volume on the Trade[XYZ] market occurs through Hyperliquid’s own application and API, while all third-party frontends combined account for only about 3%, with Trade[XYZ]’s own frontend representing just a small fraction of that. In other words, nearly every trade on the Trade[XYZ] product takes place on Hyperliquid’s interface.

This represents substantial and sustained user acquisition. Trade[XYZ] has brought over 300,000 unique wallets to Hyperliquid cumulatively, and continues to add 36,000 to 48,000 new wallets monthly, peaking near 79,000 in March during its launch and the SpaceX surge. Stock and RWA perpetual contracts serve as top-of-funnel acquisition channels: the assets act as bait, while Hyperliquid is where users land, trade, and stay. This is real attention and genuine user acquisition value—never reflected in fee tables.

Total trading fees from HIP-3 amount to approximately $37.9 million, divided into three parts. Approximately $9.2 million in builder code fees go to a third-party frontend, not the deployer; the remaining exchange fees are split 50/50 between Hyperliquid and the deployer. Thus, Hyperliquid’s protocol share, directed toward HYPE buybacks, is approximately $14.3 million, and the deployer’s share is approximately $14.3 million accrued. HIP-3 caps the deployer’s share; Hyperliquid’s protocol fee matches any portion exceeding 100% of the deployer’s share, ensuring the deployer never receives more than half. Cheap, deep markets attract the trading volume that generates fees themselves.

HIP-3 deployers select a fee structure for each market: the Standard model charges 9 basis points to takers and 3 basis points to makers, while the Growth model charges 0.9 basis points and 0.3 basis points, representing a reduction of approximately 90%. The Growth model is limited to real-world assets outside of cryptocurrency and explicitly excludes crypto-wrapped assets such as MSTR; notably, GOLD is also excluded due to overlap with the existing PAXG-USDC market. This exclusion provides us with a clear natural experiment.

Today, order book fees for growth-mode instruments are near 0.86 basis points, while excluded instruments are near 7 basis points—a eightfold difference on the same matching engine. RWA perpetuals compete on total cost with traditional finance. A 9-basis-point fee cannot compete with CME index futures or spot stock commissions, but a 0.9-basis-point fee is competitive and enables round-the-clock leveraged trading. Cheap, deep markets are how market share is won, and depth and a strong market maker base are built from this. In a category that tends toward a single winner, maximizing trading volume, open interest, user count, and reference price standing is valuable.

However, the growth model is not the reason for trading volume, as evidenced by three data points. First, on-chain comparisons: six of the other seven HIP-3 deployers use the same fee structure but have virtually zero trading volume; the second-largest deployer (dreamcash) even offers narrower spreads, yet its volume remains roughly 30 times smaller—if low fees drove volume, dreamcash should be close. Second, the GOLD experiment: GOLD pays fees approximately eight times higher than the growth order book, yet it is the single largest fee market and ranks among the top three by both trading volume and open interest. Traders are willing to pay full fees for GOLD because liquidity is there.

That’s why shutting it down won’t kill trading volume; it will redirect more value to HYPE. Since exchange fees are split 50/50 under both models, increasing fees will raise HYPE’s value by approximately 9 to 15 times (from about 0.9 basis points in growth mode to 9–12 basis points in standard mode). As a result, even with significantly reduced trading volume, Hyperliquid’s buyback share will still rise—unless trading volume collapses by more than about 85%.

At 7 basis points observed in GOLD, tradexyz would need only about 11% of today’s trading volume to match today’s buybacks (about 15% at 5 basis points, and about 25% at 3 basis points). A realistic monetization strategy involves adjusting mature markets to 5–7 basis points, while preserving half to three-quarters of trading volume due to the moat—this would channel approximately $90 million to $185 million annually into buybacks, or 3–5 times current levels. This is not hypothetical: GOLD is already operating at standard rates, converting 4.3% of trading volume into 23% of all buybacks. Scenarios shutting down growth mode have been observed in real time on a single market, demonstrating that deep, real-world asset markets maintain trading activity at standard rates, making a collapse exceeding 85% highly unlikely. These two phases represent a strategy: first, expand the moat at low cost, then monetize later—both value-driven toward HYPE: first users, trading volume, open interest, and reference price standing; then fees.

The top 30 markets account for approximately 95% of open interest, led by the S&P 500, XYZ100 Index, Brent Crude, and WTI. More interesting than the levels themselves is the speed at which each market reaches them. Measuring the number of days each market takes to reach 25%, 50%, and 75% of its current open interest since listing, the median market reaches a quarter of its final size in 9 days, half in 15 days, and three-quarters in 30 days—but the differences are vast and revealing. The fastest markets reach half their current open interest in about two weeks (SpaceX in 14 days, S&P 500 and silver around 15 days), while the earliest individual stocks listed when the venue’s liquidity infrastructure was still nascent took five to six months (Microsoft: 192 days, Meta: 159 days). This gap reflects the deployment curve: recently listed markets grow far faster than earlier batches because market-making relationships and tools are already in place on day one.

A. Market maker concentration across markets over time

As Tradexyz has matured, liquidity provision has expanded. The heatmap below shows the share of resting order volume captured by the top five market makers for each market and week. Early markets appear dark blue, with a small number of market makers providing nearly all passive liquidity in the initial months (top five shares exceeding 90%). Over time, the largest and most liquid markets have lightened in color as more market makers compete to quote, while many individual stocks remain concentrated. A more concentrated order book is not inherently bad—it is a natural part of market development—but the growing competitiveness of flagship markets is a healthy sign, indicating that liquidity provision on Tradexyz has evolved into a competitive business at the top of the order book, rather than a favor granted by one or two market makers.

B. Market Maker Main Force

A natural question is whether a few firms quote the entire market, or whether each market attracts its own specialists. Ranking the top liquidity providers over the past 30 days for each market, and identifying which wallets repeatedly appear at the top across markets, reveals a clear dominant force. The single largest liquidity provider is among the top five quote providers in 47 of the 73 markets and ranks first in 22 markets; the top three liquidity providers collectively are among the top three quote providers in 57 of the 73 markets. Several of these wallets quote all four asset classes—equities, commodities, forex, and indices—while all exhibit textbook market maker characteristics: directional exposure within one percent, and realized PnL within rounding error of zero.

Fees are driven by commodities and indices. Commodities alone account for 54% of all fees earned, indices for 24%, and the entire long tail of single stocks and foreign exchange makes up 22%, despite stocks representing the majority of listed assets. Gold is the single largest contributor, generating 23% of fees ($8.7 million), followed by the XYZ100 Index (18%), WTI Crude Oil (13%), and Silver (10%); the top ten markets generate 84% of all fees.

A subtle distinction with GOLD is that fee ranking is not the same as trading volume ranking, because fee structures vary by market—this ties back to growth models. GOLD is the only major market excluded from the growth model, so it pays approximately 7 basis points, while the rest of the order book pays around 1 basis point, making it the top fee market by this metric alone: it accounts for just 4.3% of trading volume but 23% of all fees. By trading activity, GOLD is a secondary market; by fee revenue, it is massive.

My assessment is that they cannot and, more importantly, should not do it. The strongest reason is regulation. Listing perpetual contracts for NVIDIA, TSLA, and pre-IPO SpaceX falls squarely within the realm of securities derivatives, and HIP-3 deliberately externalizes this responsibility to deployers. If the core team were to list stocks directly, it would bring the protocol, the foundation, and HYPE squarely into regulators’ crosshairs. Keeping listing at arm’s length is not a missed opportunity—it’s by design.

Other factors exacerbate this. Hyperliquid’s value lies in being a trusted, neutral infrastructure; having the core team select assets undermines the permissionless argument and the HIP-3 goal of monetizing the deployment auction fee market. Operating 92 equity, forex, and commodities markets—procuring oracles, managing market hours and halts, cultivating market makers, and executing hundreds of on-chain risk operations—is a full-fledged operational business orthogonal to building a high-performance exchange. Attracting top-tier market makers for niche RWA perpetuals is a matter of relationships and capital, not protocol engineering—and it is precisely here that even funded experts make slow progress. The empirical record addresses this: if this were easy or feasible internally, one would expect the core team to have already done it, or for there to be many strong deployers. Instead, the second-largest deployer is 46 times smaller, focused independent RWA venues are 24 to 33 times shallower, and new entrants are driving liquidity back to Hyperliquid. Scarcity is proof of difficulty.

I’d like to end this article with the analogy that has impacted me most: Tether is doing for global access to stocks what it has done for global access to the U.S. dollar. All data in this article was provided by the team at @hydromancerxyz.