Author: Mohit Pandit

Translator: Deep Tide TechFlow

Deep Tide Overview: Trade[XYZ] achieved 98% of HIP-3 trading volume on Hyperliquid, leading many to worry that it would take over. However, data shows that Trade[XYZ] built an institutional-level perpetual contract market in just eight months, bringing 300,000 users to Hyperliquid, with 97% of transactions occurring on Hyperliquid’s front end, where both parties share the transaction fees equally. This is not a threat; it is a successful validation of Hyperliquid’s strategy of “open infrastructure, allowing professional teams to compete, letting liquidity determine the winner.”

(Data as of June 2026) As the HIP-3 positions rise each time and the trading volume share leaps with each basis point, every new pre-IPO asset launch, and every tweet about Hyperliquid leading price discovery for the world's largest and most watched assets, the voice in everyone's mind is changing.

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

I intend to use data and first principles to argue why I believe Trade[XYZ] is additive to Hyperliquid and thus to HYPE as well.

The conventional argument is narrow: Trade[XYZ] locks in HYPE, launches and operates new markets, generates trading fees, and recycles fees back to HYPE for buybacks. While this is indeed true, it underestimates the relationship between Hyperliquid and deployers, specifically here, @tradexyz. The reality is that Trade[XYZ] has built the hardest thing in this category: a true liquidity market for stocks, indices, commodities, and forex perpetual contracts over eight months, proving that HIP-3 can support institutional-grade liquidity in non-crypto perpetual contracts built by professional teams while Hyperliquid retains users, matching engine activity, fee-sharing, auction demand, and ecological narrative without directly assuming listing or regulatory responsibilities.

There are two paths to building a large derivatives exchange

The vertical path is to build all markets, acquire assets, operate oracles, recruit market makers, assume risks, and monopolize profits. Lighter and Ostium (pure RWA) are vertical integrated products. The horizontal path is to provide the underlying, allowing permissionless deployers to build markets on top and share transaction fees. This is Hyperliquid’s HIP-3, and @tradexyz is one of its deployers. However, understanding HIP-3 purely as horizontal is a mistake. The correct way to understand it is: this is an access application.

Hyperliquid’s belief is that the sustainable advantage of on-chain finance lies in core infrastructure—L1, clearinghouses, matching engines; the core team puts almost all its effort into this. The bet is that the best operators will choose to build on this infrastructure, and to attract top operators, it needs to continuously evolve towards high performance and neutrality. There is only one CME Group, one NYSE, and one Hong Kong Stock Exchange in the world. Liquidity attracts liquidity; a category without a single deep liquidity winner has essentially lost. Hyperliquid’s ambition is to become the main venue for all finance, becoming the neutral foundation upon which various category winners build, and HIP-3 is the mechanism to achieve this. It does not designate winners but opens the track, inviting the best operators to compete to create the deepest markets, letting liquidity itself decide. The ultimate winners will bring immense value back to Hyperliquid: transaction fees, buybacks, users, while retaining true rewards themselves. From this perspective, concentration is not a failure of the model; it is how the model operates according to the conventional ways of finance.

Nonetheless, there are many dissenting opinions about this model, and I think they should be heard fairly.

The first is that Hyperliquid is giving up future value, letting deployers keep about half of the fees and own the rights, foregoing revenues it could have captured by building its own stock perpetual contracts. The second, sharper point is that HIP-3 is disguised vertical integration. One deployer accounts for about 98% of HIP-3 trading volume, leading to allegations of favoritism (often directed at the relationship between Trade[XYZ] and the Unit ecosystem), while Hyperliquid still takes 50% of the fees.

My view is that this greatly underestimates how difficult it is to build an institutional-grade real-world asset market. The entire objective of this report is to present a data-supported, first-principle analysis: whether this current model has even a semblance of success.

What does it take to build a stock perpetual contract market?

The most common misunderstanding of this business is "just launch the assets directly." Launching is the easy part; the challenge and the moat lie in enabling the newly launched market to trade at large volumes. Trade[XYZ]’s data points to three clear challenges: 1. Launching fast enough to capture demand 2. Acquiring market makers that create depth 3. Keeping the liquidity economically real and maintaining daily operations of these markets.

Speed of launch

A perpetual contract market only has value if it exists when traders are thinking about it. Measuring from the on-chain registration of each asset to the first transaction, Trade[XYZ]’s median launch time is just 3.3 days, with 65% of markets launching within a week and 47% within three days.

A tradeable market is the true moat

Trade[XYZ]’s depth is both deep and well-distributed. The flagship index and commodity markets have institutional-level order book depths, with $2.6 million in orders within 10 basis points of the mid-price for XYZ100, $964,000 for the S&P 500 market, and $759,000 for gold, while individual stocks like Nvidia and Tesla also boast sufficient trading volume. In contrast, the median market has only about $20,000 in orders within 10 basis points. This illustrates how rational market makers allocate capital.

Acquiring market makers is the true skill, and the presence of market makers tightens markets. In the 73 markets with sufficient data, the correlation of the number of different market maker wallets per day with spreads is -0.72, trading volume with spreads is -0.82, and trading volume with open interest is +0.96. The volume-weighted average spread across all ledgers is 2.33 basis points, with a daily turnover approaching 2.9 times the open interest. Trade[XYZ]’s advantage lies in acquiring market makers' BD work and capital work, which creates a tight and deep market.

It is worth asking from first principles why acquiring this liquidity is challenging, and why only one deployer has successfully scaled these markets. Market makers earn spreads, but can only survive by managing what remains on the books after each transaction. In simple terms, market makers need hedging methods. The primary risk is pure inventory risk: each transaction turns the trading desk into either a long or short position, and the unhedged trend is a red flag. For stocks, the key is hedging. Crypto perpetual contracts can hedge at another crypto exchange around the clock, but the only real hedge for stock perpetual contracts is the underlying stocks, ETFs, or futures, which only trade during spot market hours. During regular market hours, a trading desk can hedge its TSLA perpetual contract inventory with TSLA stock, capturing spreads with almost no risk, allowing for tight and deep pricing. But when the market closes, it holds raw inventory, and the rational response is to widen spreads, reduce depth, or stop quoting. There is no hedging before the IPO, which is why those ledgers are so thin prior to listing. Additionally, there is adverse selection (greater shares of informed trading occur in after-hours flows), funding rates, and holding costs (funding rates must tether perpetual contracts to the index without making hedging uneconomical), along with oracle or gap risks (perpetual contracts settle according to for oracle, and stale, manipulable, or gapped marks present uncontrollable liquidation risks that prevent the books from making markets at scale).

Discovery Bounds keep marked prices within the maximum leverage of the reference price for one times either direction (20 times leverage is about 5%), re-anchoring at a discrete, market-capped step size, becoming a hard ceiling until external pricing returns, combined with liquidation protection preventing liquidations when the liquidation price is outside active bounds. In simple terms, how far a single move in price can go has a “known upper limit”; exchanges will not liquidate the trading desk within that limit, hence the worst-case scenario for unhedged overnight inventories is bound and quantifiable, rather than open-ended. Finally, each market's funding rate multiplier scales standard funding rates by 0.5 (approximately 5.5% annual baseline), but pre-IPO varieties drop to 0.005. The funding rate tethers perpetual contracts to fair value without squeezing market makers, and for pre-IPO varieties with no stocks for arbitrage, it nearly completely shuts off, making holding positions themselves not unprofitable. All of these together form a toolbox for markets that cannot be made without hedging, according to first principles.

Measuring the order book depths of the top ten stocks at various times, overnight depth maintains at about 116% of the levels during spot hours; individual stocks like Nvidia and Tesla have even deepened because perpetual contracts are the only active prices after the spot market closes. On weekends, even index futures close and hedges evaporate for two whole days, reducing depth to about 37%. It should be honestly noted as a boundary: this gives Trade[XYZ]’s after-hours ledger resilience, but not magically superior. The lasting differentiator remains its daytime depth, order flow, and truly difficult-to-make markets breadth. The data supports that Trade[XYZ]’s risk mechanism allows market makers to retain depth overnight, while first principles predict a collapse, which is itself an extraordinary engineering achievement that enables these markets to be made.

Trade[XYZ] is not a one-off launch business

Trade[XYZ] does not walk away after launching. In approximately 300 recent on-chain operation windows, it executed 294 different risk management operations. This includes 54 changes to position limits, 35 switches to growth modes, 34 adjustments to funding rate multipliers, 28 trading pauses, and 11 margin mode changes, along with asset marking. This is an ongoing, market risk management across 92 underlying assets, handling real trading hours, pauses, and funding rates; it is a full-time market operation business.

The difficulty can best be understood through comparison. Tokenized spot stocks (xStocks) on Solana represent over $25 billion in total trading volume, yet actual DEX trading volume is only about $517 million. Ostium is a dedicated, capitalized RWA perpetual contract DEX with a cumulative trading volume of about $59 billion, but its open interest is only about $11.5 million, which is 1/24 of Trade[XYZ]. New entrants like Variational do not even attempt to build native depth but aggregate liquidity through RFQs from Hyperliquid, Lighter, and centralized exchanges, routing to Hyperliquid to access liquidity being discussed. The leader in on-chain stock perpetual contracts by a significant margin is Trade[XYZ] on Hyperliquid.

Trade[XYZ] expanded the Hyperliquid user base, benefiting from its network effects

The natural assumption is that deployers own users through their own frontend. The truth is quite the opposite. Marking every trade generates its frontend (builder) code, measuring at the taker side, or the party selecting the frontend, shows that about 97% of Trade[XYZ]'s market trading volume occurs through Hyperliquid’s own applications and APIs, while all third-party frontends only account for about 3%, and Trade[XYZ]'s own frontend is just a small part of that. In other words, almost every trade on Trade[XYZ] products happens within Hyperliquid’s interface.

This represents significant and ongoing customer acquisition. Trade[XYZ] has brought Hyperliquid approximately 300,000+ different wallets, which are still increasing by 36,000 to 48,000 per month, peaking at nearly 79,000 in March during the launch and SpaceX surge. Stocks and RWA perpetual contracts serve as customer acquisition channels at the top of the funnel: the assets are bait, and Hyperliquid is the venue where users from this funnel land, trade, and stay. This represents true attention and user acquisition value that will never show up on a fee table.

Incentives at the protocol level are correctly aligned

HIP-3 total trading fees are approximately $37.9 million, split into three parts. About $9.2 million of builder code fees go to third-party frontends, not the deployers; the remaining exchange fees are split 50/50 between Hyperliquid and deployers. Therefore, Hyperliquid’s protocol share directed to HYPE buybacks is about $14.3 million, and the deployer’s share is about $14.3 million as well. HIP-3 sets a cap on deployer shares; Hyperliquid’s protocol fees match any deployer share over 100%, so deployers can never receive more than half. Cheap, deep markets attract the volume that generates fees themselves.

My view on the growth model

HIP-3 deployers choose fee structures 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, a reduction of about 90%. Growth mode is limited to real-world assets that are non-crypto, explicitly excluding crypto-wrapped products like MSTR; notably, it also excludes GOLD due to overlap with existing PAXG-USDC markets. This exclusion provides us with a clear natural experiment.

Today, the rate for order books complying with growth mode is about 0.86 basis points, while the excluded varieties have rates close to 7 basis points, reflecting an eight-fold gap on the same matching engine. RWA perpetual contracts compete with traditional financial costs. A 9-basis point fee cannot compete with CME index futures or spot stock commissions, while 0.9 basis points is competitive and can accommodate leveraged trading around the clock. Cheap, deep markets are the way to gain market share, and depth and market maker bases are formed from this. In a category that tends toward a single winner, maximizing trading volume, open interest, user count, and reference price status is valuable.

However, the growth model is not the reason for trading volume existence; three data points prove this. First is the on-chain comparison: six of the other seven HIP-3 deployers have the same fee tools but essentially zero trading volume, with the second-largest deployer (dreamcash) even quoting narrower spreads, yet the scale remains about 30 times smaller; if low fees could bring trading volume, dreamcash should be close. The second is the GOLD experiment: the fees paid for GOLD are about eight times that of the growth order book, yet it is the largest single fee market, ranking in the top three by trading volume and open interest. Traders are willing to pay full fees for GOLD because the liquidity is there.

This is why shutting it down will not stifle trading volume; it will direct more value towards HYPE. Since exchange fees are split 50/50 in both models, raising fees will increase HYPE's value by about 9 to 15 times (from the growth model at about 0.9 basis points to the standard model at about 9-12 basis points), ensuring that even with a significant drop in trading volume, Hyperliquid's buyback share will rise unless trading volume collapses beyond about 85%.

At the observed 7 basis points, tradexyz only needs about 11% of today’s trading volume to match today’s buyback volume (about 15% at 5 basis points, about 25% at 3 basis points). A realistic monetization scenario is adjusting mature markets to 5 to 7 basis points while retaining half to three-quarters of trading volume due to moat preservation, which could deliver about $90 million to $185 million back to buybacks annually, three to five times the current level. This is not a hypothesis: GOLD has already operated at standard rates, converting 4.3% of volume to 23% of all buybacks. The scenario of shutting down the growth model has been observed in a single market in real-time, demonstrating that deep real-world asset markets maintain trading under standard rates, making a collapse beyond 85% unlikely. These two phases represent a strategy of now expanding the moat at low costs and later monetizing, both directing value towards HYPE: first user acquisition, trading volume, open interest, and reference price status, then fees.

Market dynamics

The top 30 markets hold about 95% of open interest, led by the S&P 500, XYZ100 index, Brent crude oil, and WTI. More interesting than the levels is how fast each market reaches those levels. Measuring the number of days from listing to reach current open interest levels of 25%, 50%, and 75%, 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 disparities are large and revealing. The fastest markets reach half of their current open interest in about two weeks (SpaceX 14 days, S&P 500 and silver about 15 days), while the earliest single stocks listed when the venue’s liquidity infrastructure was still in its infancy took five to six months (Microsoft 192 days, Meta 159 days). This gap is a specific reflection of the deployers’ learning curve: recently listed markets grow significantly faster than earlier batches because market maker relationships and tools exist from day one.

Proof of market quality

A. Market maker concentration changes over time

As Tradexyz matures, liquidity provision has expanded. The heatmap below shows the proportion of order book trading volume occupied by the top five market makers for each market and each week. Early markets appeared deep blue, where in the initial months, a small number of market makers provided nearly all passive liquidity (with the top five accounting for over 90%). As time passes, the colors of the largest, most liquid markets become lighter as more market makers compete to quote, while many individual stocks remain concentrated. A more concentrated order book is itself not a bad thing; it is how markets are guided, but the increasing competition for flagship markets is a healthy sign that liquidity provision on tradexyz is now a competitive business at the top of the order book rather than the benevolence of a few market makers.

B. Major market maker presence

A natural question is whether a few companies are quoting the entire market or whether each market attracts its own specialists. Ranking the top order makers for each market within 30 days, and inquiring which wallets repeatedly appear at the top of various markets reveals a clear major player. The single largest major player wallet is in the top five order makers for 47 out of 73 markets, ranking first in 22 markets; the top three major player wallets combined are in the top three order makers for 57 out of 73 markets. Several of these wallets simultaneously quote across all four asset classes: stocks, commodities, forex, and indices, all exhibiting textbook market maker characteristics: directional positions within one percent, realized PnL within rounding error of zero.

Sources of fees

The fee base is driven by commodities and indices. Commodities alone account for 54% of all earned fees, indices for 24%, and single stocks and forex represent the entire long tail accounting for 22%, even though stocks comprise most listings. Gold is the single largest contributor, accounting for 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 subtlety imposed by GOLD is that the fee rankings do not align with trading volume rankings, as fee structures vary by market, which circles back to the growth model. GOLD is the only large market excluded from the growth model, hence it pays about 7 basis points, while the remainder of the order book pays around 1 basis point, making it the top fee market: it only accounts for 4.3% of trading volume but represents 23% of all fees. Calculating by trading activity, GOLD is a minor market; by buyback fuel, it is enormous.

Can the core team do this themselves?

My assessment is that they cannot, and more importantly, they should not. The strongest reason is regulatory. Listing perpetual contracts for NVIDIA, TSLA, and pre-IPO SpaceX falls entirely in the realm of securities derivatives, and HIP-3 intentionally externalizes that responsibility to deployers. If the core team were to list stocks themselves, it would bring the protocol, foundation, and HYPE directly into the sight of regulators. Keeping listings at arm’s length is not a missed opportunity; it is by design.

The remaining reasons compound this. Hyperliquid’s value lies in being a credible neutral infrastructure; the core team selecting assets would undermine the permissionless argument and the deployment auction fee market that HIP-3 aims to monetize. Operating 92 stock, forex, and commodity markets, sourcing oracles, managing market timing and suspensions, nurturing market makers, and executing hundreds of on-chain visible risk operations is a full operational business orthogonal to building a high-performance exchange. Competing for first-rate market makers for niche RWA perpetual contracts requires relationship and capital work, not protocol engineering; even funded experts progress slowly in this regard. Empirical records address this issue: if this were easy or could be accomplished internally, one would expect the core team to have already completed it or there to be many strong deployers. Instead, the second-largest deployer is 46 times smaller, and specialized independent RWA venues are 24 to 33 times shallower, with new entrants routing liquidity back to Hyperliquid. Scarcity is the proof of difficulty.

I would like to conclude this article with an analogy that has influenced me the most. What Tether has done to acquire dollars globally, it is doing for global equities.