Deep Liquidity: The Structural Brake on Real-World Assets Growth

Behind all of this lies liquidity, the silent force that determines whether a market merely exists or truly functions. 

Deep liquidity is what turns thin, fragile markets into scalable financial ecosystems. It is what attracts capital at scale, allowing large participants – often referred to as "whales" - to operate without distorting prices. 

But executing size is never trivial. Even across the largest crypto venues, liquidity can quickly become a constraint for some players.  

This structural friction underpins the continued relevance of Over-the-counter (OTC) desks in crypto markets. By sourcing liquidity from multiple counterparties and executing transactions off-book - often distributing orders over time to smooth entry or exit - OTC desks help facilitate large trades with reduced market impact, even for highly liquid assets such as Bitcoin. 

However, this machinery does not scale evenly across the crypto landscape. 

In niche segments operating in already small markets, liquidity management becomes far more complex. And this is where the limitations of the Real-World Asset (RWA) sector begin to surface. 

RWA growth masks a structural issue 

At first glance, the RWA narrative appears compelling. 

The sector has expanded sharply, posting +242.4% growth over the past year, driven by tokenized commodities (~x4 growth), mostly pushed by underlying performance, and tokenized money market funds, which together account for roughly 60% of total RWA market capitalization, according to RWA.xyz data. 

Yet headline growth obscures a deeper structural weakness. 

Despite rising issuance, secondary market liquidity remains thin, uneven, and fragmented. Unlike Bitcoin or major crypto assets - where OTC infrastructure and deep centralized venues absorb large flows - RWA liquidity is scattered across multiple blockchains, isolated venues, and a mix of centralized and decentralized platforms.  

And fragmentation has a cost.  

Bid-ask spreads widen. Market impact increases as traded notional rises. And in such conditions, the very capital that tokenization aims to attract remains structurally sidelined, particularly when tokenized assets are expected to work as collateral – where lenders must be confident in their ability to liquidate positions reliably when needed. 

For this to happen, market makers have to step in to provide liquidity. But the latter allocate capital where inventory can be deployed efficiently - able to adjust risks in real time and execute exits with minimal frictions - a condition most tokenized assets do not meet so far.  

Liquidity provision in that segment typically requires pre-funded capital, off-chain settlement through custodians, and delayed minting and redemption, leaving market makers’ inventories effectively illiquid and forcing them to carry risk across market swings at a high opportunity cost. Until these constraints are addressed, trading activity and market depth are likely to remain structurally constrained. 

Fragmented liquidity in early financial markets 

To understand the current positioning of tokenized asset markets, it is useful to step back several decades, to the early stages of the financial markets we now take for granted. 

Financial history offers a clear lesson: liquidity does not emerge instantly, but is built progressively through integration, standardization, and institutional coordination. 

In the early equity and bond markets, trading venues operated largely in isolation. Each exchange operated as a siloed liquidity pool, fragmenting order flow and limiting effective arbitrage. As a result, price discovery was slow and inefficient, with the same securities often trading at different prices across venues. 

Before the advent of electronic trading, market-wide regulation, and centralized clearing, this fragmentation translated into wider spreads, higher transaction costs, and structurally shallow liquidity.  

In that sense, the RWA ecosystem closely mirrors what was observable back then: growing in issuance, rich in promise, but constrained by structural frictions that prevent liquidity from compounding. The latter requires time, infrastructure and alignment, while the former is a matter of polished engineering. 

Tokenized asset execution in practice: Centralized venues 

To contextualize liquidity conditions in tokenized assets segment, we have to assess two key points:

• Market depth - how much size the market can absorb without significant price movement.
• Slippage - difference between the expected execution price and the realized one across increasing traded notional sizes.

This Sandmark analysis focuses on tokenized gold - Paxos Gold (PAXG) and Tether Gold (XAUT), as other segments, such as tokenized equities, remain too small to offer meaningful market depth on centralized venues.  

Indeed, for tokenized Nasdaq (QQQx) or S&P500 (SPYx), both buy and sell orders of institutional size trigger immediate price dislocations. Market impact rapidly reaches ~25%, reflecting a near-absence of resting liquidity. 

Beyond $500k, execution becomes economically unviable altogether. Order books are effectively wiped, and the resulting slippage would reduce any position to dust. 

A comparison of 30-day trading volumes across traditional (CME Futures) and tokenized markets highlights the true magnitude of the liquidity gap. 

When aggregating PAXG and XAUT, total tokenized gold volume represents roughly 0.4% of CME Gold futures volume over the same period. This figure is already striking: tokenized gold - the most liquid segment within RWAs - operates at two orders of magnitude below its traditional benchmark.  

The disparity is even more severe for tokenized equities. The combined volume of SPYx and QQQx is orders of magnitude smaller relative to the most actively traded S&P 500 instrument, the E-mini S&P 500 futures. In relative terms, the volume share of tokenized equity indices is more than 1,000x smaller than the 0.4% observed for gold - a segment that is itself already marginal at scale. 

(Source: CoinMetrics, CME Gold and CME E-mini S&P500 Futures) 

This scale mismatch directly explains why onchain execution for tokenized equity indices deteriorates far more rapidly than for gold. With such limited baseline volume, liquidity simply does not exist to absorb large trades. 

Looking across spot markets for tokenized gold, a clear execution ceiling emerges well below institutional size. While slippage remains “manageable” at smaller notionals - still orders of magnitude higher than traditional rails slippage - spot liquidity deteriorates sharply once trade size nears $500k, at which point both PAXG and XAUT exhibit slippage in the ~20% range. 

Beyond that threshold, execution quality collapses entirely: at $1mn, slippage exceeds 50% for PAXG and approaches 70% for XAUT, rendering spot markets functionally unusable for size. 

(Source: CoinMetrics, Spot 30D Average Slippage) 

This behavior highlights a critical structural weakness. The issue is not marginal inefficiency at the tails, but a lack of scalable depth. Once immediate order-book liquidity is exhausted, there is no secondary layer of participation to absorb flow. 

Futures markets, by contrast, provide a slightly better execution profile – concentrating liquidity by design in most venues. But the improvement is uneven. PAXG futures reduce slippage meaningfully at smaller sizes, but still face scalability constraints as notional grows, indicating that depth remains finite and sensitive to inventory stress. 

(Source: CoinMetrics, Futures 30D Average Slippage) 

Despite XAUT futures displaying a more robust liquidity profile, this is far from enough. The inability to execute beyond $500k without significant price disruption effectively disqualifies these assets from use cases that require predictable liquidity - including treasury deployment, collateralization, or market-neutral strategies. 

Onchain venues 

By simulating execution across the deepest Uniswap liquidity pools for tokenized gold and Jupiter for tokenized equities, a first conclusion stands out clearly: onchain liquidity is materially deeper than what is observable on centralized venues. 

For both PAXG and XAUT, onchain markets are able to absorb six-figure trades with limited slippage and even approach the $1mn threshold without immediate structural breakdown - a level where centralized spot markets already fail.  

For onchain venues, two key constraints - on top of protocol fees - must be taken into account when assessing trade execution.

The first execution layer is currency spread. Onchain trades are mostly routed through stablecoin pairs, where even minor spread from the peg becomes increasingly punitive at scale. While negligible for small trades, this conversion cost grows linearly with notional when expressed in dollars, creating a persistent drag on execution for large orders. 

The second and most important layer is the liquidity pool price impact. Even when routing through the deepest pools available, execution inevitably consumes orderbook liquidity across multiple price levels. As trade size increases, the marginal cost of liquidity rises sharply, and slippage accelerates non-linearly. 

(Source: Uniswap V3, Jupiter, as of 01.21.26 4:00 PM UTC) 

In a recent Ethereum transaction, a user swapped 47.30 PAXG (~ $228,804), for 226,471 USDC (~ $226,408), and 29.97 XAUT (~ $144,543), for 143,038 USDT (~ $142,930). In both cases, realized execution reflects ~1% slippage - including currency spread, fees from 5 to 30bps on Uniswap pools, and market impact - fully consistent with the slippage metrics observed for six-figure onchain trades. 

Tokenized equities tell a very different story. 

Even on Jupiter – one of the most dominant decentralized liquidity aggregators – where aggregations improve routing efficiency, execution capacity collapses quickly. 

Beyond mid six-figure sizes, price impact dominates, and at higher notionals, quoted execution values diverge materially from expected prices. In some cases, liquidity becomes effectively one-sided or vanishes entirely – leaving large orders in near-total value erosion – even for the most traded tokenized stock (TSLAx). 

In fact, onchain market participants show a strong preference for single-stock exposure rather than index replication. Trading volumes and liquidity in a few tokenized equities materially exceed those of tokenized indices like SPYx or QQQx - reflecting a broader onchain bias toward high-beta, narrative-driven assets, where directional conviction dominates over diversification. 

Onchain markets undeniably improve execution relative to centralized spot venues. Aggregation, composability, and continuous arbitrage allow liquidity to form more efficiently. But onchain liquidity is still finite, and its limits become apparent as we approach institutional scale. 

Tokenized assets relative to the underlying 

Beyond slippage and market depth, a third - often overlooked - constraint emerges: the spread between the tokenized asset and its underlying market. 

During volatility expansion pockets in the gold market, absolute spreads between tokenized gold and the underlying have expanded materially - reaching up to ~3% in the case of PAXG. 

These dislocations have been most pronounced during macro-driven stress events, notably during Q1 2024 as gold broke above the $2,000 threshold amid expecations of the first Fed rate cuts of the cycle, or in April 2025 following the escalation of US-China tariff war. 

Since 2024, PAXG has exhibited an average spread of ~0.48%, but this masks significant tail risk: roughly 11% of daily observations exceed a 1% spread, and around 1% exceed 2%. 

XAUT, by comparison, displays a more stable profile, with only ~2% of observations above 1%, and a maximum observed spread of ~1.40%. This relative resilience is consistent with earlier findings: deeper order books and more consistent liquidity provision dampen volatility during periods of abnormal buying or selling pressure. 

(Source: CoinMetrics, TradingView)

In highly liquid traditional markets, large flows are absorbed primarily through volume, supported by deep order books and dense participation. Tokenized markets, by contrast, operate on fragmented and significantly thinner liquidity pools. 

When sizeable orders hit onchain or centralized venues, they exert disproportionate price pressure, while the underlying market continues to clear efficiently. Although arbitrage mechanisms exist in theory, they are slow, capital-intensive, and operationally constrained in practice - particularly when spanning multiple chains, custodians, compliance layers, and settlement processes. 

As a result, tokenized assets respond to demand - or supply - shocks through price dislocation rather than volume absorption. The underlying asset remains liquid; the onchain mirror does not. Identical exposures, therefore, are exhibiting materially different liquidity properties under stress. 

What may initially be perceived as a premium for continuous trading and 24/7 settlement can turn into a structural weakness. This undermines the use of tokenized assets for applications that rely on price fidelity, notably collateralization. 

Market structure yet to materialize 

The first phase of tokenization has largely succeeded in its initial objective: bringing assets onchain. Real-world assets can now be issued, held, transferred, and priced in a native digital format. But this was only the opening act. 

The next - and far more decisive - phase for RWA segment growth lies in market structure: liquidity, financing rails, hedging instruments, and reliable exit mechanisms. 

So far, most onchain assets exist, but they are not yet functionally usable at scale. They can be held and marked to market, but they cannot be traded with size, liquidated predictably, or relied upon as robust collateral. In practice, many tokenized assets behave more like price wrappers than fully fledged financial instruments. 

Tokenization is often associated with the bridge bringing trillions of dollars in traditional assets onchain. Main assets have crossed that bridge, but market structure still remains on the far side.