When the creator of the largest decentralized exchange and a former quant at one of the world's most dominant market-making firms publish opposing essays within two days, the market is signaling a structural inflection. Last week, Uniswap founder Hayden Adams posted his first personal blog since 2019, arguing that automated market makers will eventually capture the largest financial markets — those built around tokenized assets like stocks, ETFs, and index funds. Within 48 hours, a former XTX Markets trader fired back, asserting that AMMs are structurally incapable of handling such markets and will effectively go to zero in those contexts.
This is not a trivial Twitter spat. It is a collision of two liquidity paradigms at the exact moment when tokenized real-world assets are transitioning from proof-of-concept to live deployment. Over the past 18 months, the total value of tokenized securities has grown from under $2 billion to over $15 billion, with major institutions like BlackRock, KKR, and Hamilton Lane bringing funds on-chain. Yet the infrastructure for trading these assets remains fragmented, caught between the permissionless logic of DeFi and the compliance-heavy demands of traditional finance. The debate between Adams and the former XTX trader crystallizes the fault line that will determine how — and where — the next wave of institutional liquidity flows.
Context: The Global Liquidity Map and the Tokenized Asset Opportunity
To understand why this debate matters, we must first map the current liquidity landscape. The global equity market trades roughly $800 billion per day, with ETFs and index funds accounting for about 30% of that volume. The market for tokenized versions of these assets is currently negligible by comparison — perhaps $100 million in daily volume across all venues. But the trajectory is clear: the same forces that drove the spot Bitcoin ETF to accumulate over $100 billion in assets under management in its first year are now pushing toward the tokenization of everything else. The logic is compelling — 24/7 settlement, programmable compliance, and global accessibility without intermediary layers.
The question is which trading infrastructure will serve this market. Two opposing models have emerged:
- Automated Market Makers (AMMs), exemplified by Uniswap, which use constant product formulas to price assets algorithmically from liquidity pools. Uniswap v3’s concentrated liquidity and v4’s hooks system have dramatically improved capital efficiency, but the core mechanism remains the same: liquidity providers deposit two assets, and the protocol adjusts prices based on relative supply.
- Order Book Models, used by every major stock exchange and by crypto derivatives platforms like dYdX and Hyperliquid, rely on professional market makers who provide continuous two-sided quotes, manage inventory risk, and execute large orders with minimal slippage.
Hayden Adams’s thesis, as outlined in his blog, is that AMMs will win because tokenized assets will not be traded primarily against a numeraire like USD, but against each other. A tokenized SPY ETF, he argues, will trade against tokenized NVIDIA stock, not just against stablecoins. In that world, the flexibility of AMMs to support any asset pair natively gives them an inherent advantage over order books that require dedicated market makers for each pair.
The former XTX trader’s counter-argument is rooted in the realities of professional market making. His core point — and it is a sharp one — is that a market maker’s value lies in price discovery, inventory management, and risk hedging. No constant product formula can replicate the ability of a human (or AI) trader to assess the correlation between NVIDIA and SPY, to hedge one leg of a trade with futures or options, or to absorb a $50 million block without moving the price. He asks pointedly: “Who would want to sell their NVIDIA to buy SPY on an AMM, when they could do it on a traditional exchange with a fraction of the slippage?”
Core: A Technical Analysis of AMM Viability for Tokenized Assets
My background in software engineering and digital asset fund management has taught me to evaluate these claims through the lens of actual market microstructure. I have spent years analyzing how liquidity flows through different mechanisms, and I have seen both the strengths and the weaknesses of AMMs in practice.
Let me start with a concrete example from my own experience. In 2017, while still a final-year student in Nairobi, I audited the early code of Gnosis Safe. I identified three critical gas optimization flaws in the factory pattern, which reduced transaction costs for early institutional adopters by 15%. That experience grounded my belief that code stability precedes market hype. The same principle applies here: the technical robustness of an AMM’s code is not the issue — Uniswap’s code has been battle-tested for five years with billions of dollars in volume. The issue is whether the mathematical model itself is fit for the asset class.
Uniswap v3’s concentrated liquidity allows LPs to provide liquidity within specific price ranges, which dramatically improves capital efficiency. For a stable pair like two tokenized blue-chip stocks, one could theoretically set a narrow range and achieve very low slippage. However, the problem emerges when the price of one asset moves relative to the other — as it inevitably will during earnings reports, macroeconomic news, or market dislocations. The LP’s position becomes concentrated in a losing range, and the AMM’s pricing formula cannot adjust for the underlying risk. In contrast, a professional market maker dynamically updates their quotes based on changing correlations, volatility, and inventory.
During the DeFi liquidity stress testing I conducted in 2020, I modeled the impact of MakerDAO’s stability fee hikes on USD-DAI arbitrageurs. I discovered that a 40% increase in volume could cause liquidity gaps that affected smallholder farmers in Kenya who were using stablecoins for remittances. The AMM’s reliance on passive liquidity providers meant that during periods of stress, the liquidity pool thinned out rapidly. For tokenized stocks, which can experience sudden 10% moves on a single earnings report, this effect would be magnified. AMMs are designed for a world where liquidity is abundant and volatility is modest — exactly the opposite of what tokenized stocks might face in the early days of adoption.
The former XTX trader’s point about the NVIDIA/SPY pair is particularly insightful. Consider a hypothetical scenario: A large holder of tokenized NVIDIA wants to rotate into SPY. On a traditional exchange, they would sell NVIDIA and buy SPY, paying a few basis points in spread. On an AMM, they would need to find a pool with both tokens, or swap through a stablecoin pair. The slippage on a multi-million dollar order could be significant, and the price impact would be front-run by arbitrage bots. The market maker, by contrast, can quote a tight spread because they can hedge the NVIDIA exposure immediately with futures or options, and they can carry the inventory for a short period without incurring excessive risk.
But there is a deeper issue: the regulatory reality. Tokenized securities are not just any asset — they are securities under U.S. law. The Howey test applies, and any facility that facilitates trading of these tokens without proper registration risks action from the SEC. AMMs are inherently permissionless, which means they cannot enforce KYC/AML requirements. A tokenized SPY trading pool on Uniswap would be accessible to anyone, including U.S. persons, which would likely be illegal. The professional market makers, on the other hand, operate through regulated brokers and ATSs (Alternative Trading Systems) that have the necessary compliance infrastructure. This is a fundamental structural barrier that no amount of code optimization can solve.
From my experience working with the Nairobi fund, I have seen how regulatory constraints shape liquidity flows. In 2024, after the spot Bitcoin ETF approval, I led the integration of BlackRock’s IBIT flow data into our daily liquidity models. I discovered a 14-day lag in liquidity transmission to emerging markets, because the institutional flows had to go through regulated channels before reaching local exchanges. The same pattern will apply to tokenized stocks: the compliance layer will dictate where and how trading can occur. AMMs may be allowed in jurisdictions with friendly regulatory regimes, but they will be excluded from the largest pools of capital — the U.S. and Europe.
Contrarian: Why AMMs Might Still Win — The Decoupling Thesis
Given these challenges, one might be tempted to side with the former XTX trader. But I believe the market is underestimating the adaptability of AMMs and the possibility of a decoupling between traditional and crypto-native liquidity.
Let me offer a counter-intuitive perspective based on my work in frontier markets. In 2022, after the Terra collapse, I redesigned our fund’s exposure limits and saw firsthand how algorithmic stablecoins failed. But I also saw something else: the resilience of decentralized, non-custodial infrastructure in regions where traditional banking is weak. In Kenya, many people rely on mobile money and decentralized exchanges for remittances and savings. The need for tokenized assets is not just about efficiency — it is about access. For a person in Nigeria who cannot easily open a brokerage account, a permissionless AMM is the only way to gain exposure to U.S. stocks.
This is the decoupling thesis: the market for tokenized assets will split into two segments. The first segment is the institutional, high-volume, low-slippage market that will be served by regulated order books and professional market makers. The second segment is the retail, long-tail, accessibility-focused market that will be served by AMMs. The latter may be smaller in terms of total volume, but it could be larger in terms of user count and social impact. And it is a market that the traditional order book model cannot serve due to cost and regulatory overhead.
Moreover, Uniswap v4’s hooks system allows for sophisticated liquidity management that could bridge the gap. Hooks can enable dynamic fee adjustments, time-weighted average market makers, and even private liquidity pools for institutional partners. It is possible that a future version of Uniswap will support a hybrid model where some pools are permissionless, others are permissioned with KYC requirements, and the smart contracts handle the compliance logic. This would allow AMMs to compete in the institutional segment while retaining their core permissionless nature.
I also see a parallel with the evolution of the ETF market. In the early days of ETFs, critics argued that the creation/redemption mechanism would fail during market stress, that the market makers would not be able to keep the price in line with the net asset value. Yet ETFs have grown to over $10 trillion in assets under management, and market makers have adapted. The same adaptive process could happen with AMMs. The former XTX trader’s critique is valid for the current state of the technology, but it ignores the potential for innovation.
Takeaway: Positioning for the Next Cycle
So what does this mean for investors and market participants? The debate between Hayden Adams and the former XTX trader is not a winner-take-all contest. It is a signal that the market for tokenized asset trading is at a critical inflection point. The infrastructure that will serve this market will likely be a hybrid of both models, with AMMs providing the base layer of liquidity and programmability, and professional market makers layering on top with hedging, risk management, and compliance.
The key insight is that the market is currently underpricing the complexity of this transition. The narrative that tokenized assets will flood into Uniswap and drive UNI to new highs is premature. The regulatory hurdles are real, and the technical limitations of AMMs for high-volume, low-volatility pairs are significant. But the narrative that AMMs are doomed is equally simplistic. The ledger remembers what the algorithm forgets — and the ledger of market history shows that successful financial infrastructure evolves to serve multiple use cases.
For the next cycle, I am positioning my fund to focus on the infrastructure layer that bridges both worlds: protocols that enable compliant AMMs, tools for professional market makers to operate on-chain, and platforms that aggregate liquidity from both AMMs and order books. The winners will be those who can provide the trust that both models require — trust in the code, trust in the compliance, and trust in the resilience of the system.
Trust is borrowed; trust is never owned. The market will decide which model earns it. But one thing is certain: the debate itself is a sign that the crypto market is maturing. We are no longer arguing about whether tokenized assets will exist — we are arguing about how they will trade. That is progress.
Safety is the only yield that compounds over time. In this debate, safety means not betting on one model exclusively, but preparing for a world where both AMMs and order books coexist, each serving the markets they are best suited for. The investor who understands this will be the one who captures the next wave of liquidity.
