Intro

Welcome to the fourteenth edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to 563, James, Diego, and Oğuz for contributing to this issue.

Setting the Scene

Over the past year, Hyperliquid has quietly grown beyond its original category. What began as a high-performance perpetuals DEX has evolved into a full-stack financial platform, with liquidity, token issuance, and outcome markets all integrated into a single venue.

Still, perpetuals account for the majority of activity, and that metric alone no longer captures the full picture. Hyperliquid has been steadily adding new layers to the stack, and those pieces are starting to reinforce each other.

This issue examines four fronts: Vaults, the platform's pooled trading layer; HIP-3, a framework for permissionless perpetual market creation; HIP-4, an outcome market experiment targeting the prediction market category; and USDC on Hyperliquid, a stablecoin integration that may unlock the next phase of growth.

User-curated Vaults

563 | Dashboard

User-curated vaults crossed $80M in AUM, with the top 10 controlling 62% of TVL

A Hyperliquid vault functions like a managed trading pool: a vault leader runs the strategy, depositors allocate capital, and profits are distributed pro rata, with a 10% performance fee paid to the leader.

For now, user vaults on Hyperliquid remain fairly limited in scope. They can only trade native Hyperliquid crypto perps, with no access to spot, HIP-3, or HIP-4 markets. Even with those constraints, growth has been steady. AUM has more than doubled over the past year, rising from $38.9M to $81.9M as of June 2026, after peaking at $92.3M in September 2025.

Concentration, though, is still high. Of roughly 400 active vaults, the top 10 account for 62% of total AUM ($51M). The leading vault alone holds 17.6% ($14.4M), while the top three together represent 35.5%. At the same time, 342 of these vaults were launched in 2025 or later, which suggests the ecosystem is still early.

What now looks like a rudimentary "pod-shop-as-a-service" model has the potential to evolve into something much more institutional once additional utility comes online, including additional markets, control over fee parameters, lock-ups, transparency, and privacy. In the end, the vault interface itself is the core asset. It acts as a discovery and trust layer, enabling funds and traders to monetize alpha onchain rather than routing that activity offchain.

HIP-3 Markets

James | Dashboard

83.5% of HIP-3 traders also trade Hyperliquid's native crypto perps

HIP-3 may be a new product, but the traders are not new. 8,343 wallets account for roughly 96% of HIP-3 volume, and 83.5% of them also traded Hyperliquid's native crypto perps.

Across a sample of these dual-venue wallets, the trading behavior looks nearly identical: median trade size of roughly $160K vs $170K, and win rate of 50% vs 48%. The bigger difference shows up in how risk is managed. On native perps, these wallets peg leverage at the cap, running 100% utilization and cross-margin, with only 6% of positions isolated. In other words, they borrow the maximum the market allows, and nearly all positions share one collateral pool, so a loss on any single trade can pull margin from the rest of the account.

HIP-3 looks different. The same wallets use just 55% of available leverage and ring-fence 78% of positions in isolated margin. They borrow only about half of what they are allowed, and they keep most trades separated, so if one position is liquidated, it only loses its own collateral instead of putting the whole account at risk. This restraint is a choice. No rule requires isolated margin, and HIP-3 allows higher leverage than native perps. Put simply, the same traders adopt far more TradFi-style risk discipline the moment they trade tokenized stocks, gold, and oil.

HIP-4 Markets

Diego | Dashboard

HIP-4 crosses $161M in cumulative volume as open interest hits a $399M ATH

Launched on May 2, 2026, Hyperliquid's native onchain outcome market layer has scaled rapidly. In just 46 days, HIP-4 has generated more than $161M in cumulative volume across 2.91M trades, while open interest reached an all-time high of $399M on June 16, up 69x from $5.76M on day one.

Growth has been nonlinear. After a mid-May plateau at around 10 active markets, both volume and open interest re-accelerated sharply. The number of active markets expanded from 10 to 67 on June 6, 2026, and surpassed 150 a week later, largely driven by the rollout of 2026 World Cup markets.

The $161M in cumulative volume also masks a clear split in trader behavior across market types. Price binary markets dominate, accounting for 71% of total volume ($114M) across 2.42M trades, with an average size of $55. Standard binary markets, by contrast, have generated $10M across just 28.6K trades, with an average trade size of $482, nearly 9x larger. The result is two distinct liquidity and risk profiles emerging across market categories.

Editor's note: HIP-4 supports three market types. Price binary markets ask whether an asset will trade above or below a specific level at a set time (e.g. BTC ≥ $62,720 at June 18, 06:00 UTC). Binary markets are straightforward yes/no outcome questions without a price component (e.g. Will the Fed cut rates in June?). Categorical markets offer three or more mutually exclusive outcomes (e.g. 2026 World Cup Champion) with one position corresponding to each outcome.

USDC on Hyperliquid

Oğuz | Dashboard

USDC supply on HyperEVM increased 3.6x over the past four weeks, with ~85% now concentrated in Coinbase's AQAv2 wallet

Following Coinbase’s USDH acquisition on May 14, 2026, USDC activity accelerated materially. Mint and burn volume increased by $3.77B, bringing the 10-month total to $5.25B. Over the same period, TVL on the Arbitrum bridge fell by approximately $2B, signaling a shift in where liquidity is being held and managed.

This is not just a jump in USDC usage within HyperCore. It is a structural migration of the liquidity layer, shifting from bridge-based flows on Arbitrum to treasury wallets on HyperEVM. Coinbase and Circle treasury wallets now account for approximately 95% of total USDC supply on HyperEVM.

That shift intensified last week when Coinbase activated its AQAv2 wallet, a framework that defines the roles of technical and treasury deployers while introducing greater transparency around yield, staking, and slashing. As part of this rollout, Coinbase transferred $4.4B in USDC from a Circle-controlled address to its own, marking the largest USDC transfer on record.

Closing Thoughts

What began as a perp DEX built to bring the centralized-exchange experience onchain, without venture backing, has evolved into one of the most structurally distinct platforms in crypto. Hyperliquid did not just compete on performance. It is testing how much of the financial stack can be vertically integrated into a single venue.

With HIP-3 enabling permissionless creation of perpetual markets and HIP-4 introducing onchain outcome markets, Hyperliquid is moving beyond a trading venue into a platform for market creation. The USDC integration, particularly Coinbase's involvement, reinforces that shift. Together these changes mark a new phase of growth, and a new set of dependencies.

The competition is converging from both sides. Hyperliquid is expanding from perps into outcome markets through HIP-4, while the prediction market leaders move the other way. Kalshi launched CFTC-regulated crypto perps in May 2026, and Polymarket is building its own perps product. The open question is whether Hyperliquid's vertically integrated model delivers durable product-market fit, or whether the market fragments across multiple players competing for the same flow.

What We’re Watching

• How Anthropic enables self-service data analytics with Claude

• Strategy’s $STRC preferred stock fell to a record low

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Staff Data Analyst at Polymarket

• Data Analytics Manager at Binance

• Senior Data Engineer at CoinDesk

By Diego Cabral

The article is also available on X.

Setting the Scene

Kalshi CEO Tarek Mansour calls prediction markets “quintessential truth machines.” Polymarket CEO Shane Coplan goes further, calling his platform "the most accurate thing we have as mankind right now." These claims are bold, and the data largely supports them.

But accuracy is only half the story. The other half is about who actually produces it, who pays for it, and whether the "wisdom of the crowd" these platforms credit has anything to do with it.

The Accuracy Is Real

According to Alex McCullough's Dune dashboard, Polymarket is correct 90.4% of the time four hours before resolution. Twelve hours out: 81.2%. One day: 75.2%. One week: 78.3%. One month: 85.6%.

Raw accuracy is only part of the picture. The Brier score measures how closely a forecast matches reality, capturing not just whether it called the right side, but how confident it was. It runs from 0 (perfect) to 1 (perfectly wrong). Polymarket posted a Brier score of 0.0769 over the last two weeks. A coin-flip forecaster who calls everything 50/50 scores 0.25. Polymarket's 0.0769 is more than three times better, showing its prices usually carry real information, not only guesses.

The probabilities also align closely with reality. When Polymarket prices an event at 70%, it happens about 70% of the time. When it says 30%, the event happens about 30% of the time. That consistency is genuinely rare. Most forecasters, human or institutional, fail it.

As Andrew Courtney, a former derivatives trader and Good Judgment Project superforecaster, notes, the raw ‘N hours out’ accuracy figures are a coarse metric, tracking only whether markets priced above 50% resolved yes. The Brier score, the standard used in academic forecasting research, is more rigorous. It captures both confidence and precision, penalizing both errors and overconfidence.

The theory behind prediction market accuracy is decades old. Friedrich Hayek argued in 1945 that markets aggregate dispersed knowledge better than any central planner. Robin Hanson extended the idea in 2000, arguing markets could predict outcomes well enough to guide real decisions. In 2007, a group of economists including Nobel laureate Kenneth Arrow backed prediction markets as a serious forecasting tool.

The logic is simple. Give people with real information a financial incentive to act on it, and prices will reflect the truth.

The question is whether it works that way in practice, and who is actually behind the accuracy.

It Is Not the Crowd

The conventional answer points to the crowd.

Kalshi says its markets "leverage the wisdom of crowds," aggregating the knowledge and insights of a diverse group of participants. Polymarket attributes its edge to the "collective intelligence" of diverse traders. Both echo the Francis Galton story, where the averaged guesses of a crowd land closer to an ox's true weight than any individual expert.

The data tells a different story. A working paper published in April 2026 by researchers from London Business School and Yale University tested this claim directly using the full transaction history of Polymarket from January 2023 to December 2025, which covers 1.72M accounts and $13.76B in trading volume.

Their conclusion: prediction market “accuracy is driven by a small minority of informed traders.”

To separate skill from luck, the researchers developed a statistical test that randomizes the direction of each trader’s actual trades 10,000 times, generating a baseline of what random trading would have produced. Traders whose real profits significantly exceed that baseline are classified as genuinely skilled.

The result: only 3.1% of accounts are classified as skilled winners.

The rest break down as follows:

• 29.0% are lucky winners, with positive returns but no statistical evidence of skill

• 61.4% are unlucky losers

• 6.4% are unskilled losers, trading consistently in the wrong direction

• 0.1% are market makers

That 3.1% is not just a minority. It is what powers the entire “wisdom of the crowd.”

As a whole, the crowd adds noise, not real information.

This pattern is not unique to financial prediction markets. Research by the team behind the Good Judgment Project found the same structure in non-financial forecasting. A small elite of ‘superforecasters,’ selected purely by past accuracy, outperformed regular forecasters by roughly 60% on Brier scores. Their edge grew over time rather than regressing.

The informed minority is not unique to Polymarket. Academic evidence suggests the same structure appears across competitive forecasting environments.

Skill Persists

The same paper finds "an unusual degree of skill persistence in prediction markets." Among traders classified as skilled in one half of the data, 44% remained skilled in the other half. By comparison, skill in active mutual funds persists at just 10%, meaning prediction market skill is more than four times stickier than professional fund management.

This matters for what prediction market accuracy actually means. Prices are not accurate because thousands of small contributions cancel out the errors. They are accurate because a small, persistent group of skilled traders corrects mispricings and gets paid for doing so.

Who Pays for the “Truth”

If 3.1% of accounts generate the information, the remaining 96.9% provide something else: capital and volume.

An analysis by Andrey Sergeenkov, also covering the full trading history of all Polymarket addresses, puts a dollar figure on this dynamic. Sergeenkov calculated realized PnL across all USDC flows. The result: 84.1% of Polymarket traders lose money.

The concentration at the top is severe:

• Only 2% of all 2.5M accounts have ever made more than $1K in lifetime profit

• 0.32%, roughly 8,000 addresses, have made more than $10K

• 0.03%, or 840 addresses, have made more than $100K

Monthly sustainability is even harder:

• In any given month, fewer than 1% of accounts earn more than $5K

• Two months in a row: 0.1%

• Three consecutive months: 0.03%

• Four months running: 0.015%

Among accounts that average more than $5K in profit per month, 53% achieved it in a single month only. Just 2.6% sustained it for longer than a year.

One important nuance matters here. Raw profit and genuine skill are not the same thing. The London Business School and Yale paper shows that among the top traders ranked by realized profits, only 12% overlap with the accounts statistically classified as skilled. Making money on Polymarket is not necessarily proof of skill. Many profitable accounts are simply lucky, and the data suggests that luck does not persist. Among traders classified as lucky winners in the first half of the data, 60% became losers in the subsequent period.

Most Volume Produces "Belief," not "Truth"

There is another dimension to this story, one that complicates the “truth machine” narrative further.

Dan Schwarz, former CTO of Metaculus, published an analysis of Kalshi and Polymarket. His finding: over 80% of Polymarket's trading volume is concentrated in sports, cryptocurrency prices, and election betting. On Kalshi, roughly 90% comes from sports alone.

This is consistent with what Nexus published in March 2026, where sports and crypto alone represented 82.5% of all volume in February 2026 on Kalshi and Polymarket combined.

The distinction matters. A sports bet or a crypto price market is not necessarily an attempt at truth-seeking, and it is not aggregating knowledge at all. It can simply represent a belief or preference expressed as a wager. In this scenario, the "truth machine" claim applies, at best, to the narrow slice of markets designed to inform decisions in the first place.

Schwarz defines "useful" markets as those with real potential to inform decisions: geopolitical risk monitoring, policy outcomes, accountability for public claims, interpreting economic news, and generating new information. After filtering out sports, crypto, and entertainment, he identifies roughly 6,800 markets as potentially valuable, out of approximately 194,000 across both platforms.

Among those useful markets, accuracy improved steadily through early 2025, then plateaued. Median volume per useful market has since declined, from a peak of $81K to $42K. For markets resolving in under 90 days, Schwarz finds no statistically significant relationship between trading volume and accuracy.

Some categories work as intended. Schwarz identifies geopolitical risk monitoring as an area where the markets work as advertised: nearly $3.8B in volume across 2,821 markets, increasingly cited by mainstream media. Still, the median useful market has experienced declining volume.

Schwarz concludes that the accuracy Polymarket advertises on its homepage is real, but concentrated in a narrow slice of markets that very few participants actually trade.

What the Data Tells Us

Comparing accuracy across platforms and categories is harder than it looks. Some markets are simply more predictable than others. A coin-flip market has no "wisdom" to aggregate regardless of who trades it. So a high accuracy score does not always mean skilled forecasting.

There is one more layer worth acknowledging. Prediction market contracts have a structural ambiguity problem that goes beyond question difficulty. Traders frequently do not fully understand what they are betting on, and resolution becomes a question of rule interpretation rather than “truth”. Anyone with a background in contract law will recognize the pattern. Vague drafting plus discretionary interpretation equals disputes. In prediction markets, that discretion sits with UMA token holders, a mechanism that remains contested.

With those caveats in mind, four independent datasets still point to the same conclusion.

• McCullough's dashboard confirms Polymarket's forecasts are accurate.

• Schwarz's analysis shows most volume sits in entertainment markets while useful-market accuracy has plateaued.

• Sergeenkov's data shows 84.1% of traders lose money.

• The London Business School and Yale paper identifies the mechanism: a persistently skilled 3% drives the real price discovery, while everyone else funds them.

None of this means the platforms are broken. The accuracy is real, and the markets work as designed. In specific domains, these markets produce genuine signal and deliver it faster than traditional forecasting.

But “truth machine” and “wisdom of the crowd” are a marketing claims.

The data says something more precise. Prediction markets are accurate forecasting tools for a narrow set of questions, built on a platform that operates primarily as a gambling product, where a small, persistently skilled minority extracts value from the majority who provide capital, volume, and noise.

A skilled minority of around 3% does the forecasting. A fraction of a percent earns a living from it. Everyone else funds them.

The crowd does not produce the wisdom. It finances the people who do.

What We're Watching

• The State of International Stablecoins on Base

• USDH: What Coinbase Actually Bought

• The Race to Trade Everything

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Data Analytics AI Engineer at Fireblocks

• Lead Data Engineer at Galaxy Digital

• Crypto Quant Researcher at Citadel Securities

Intro

Welcome to the twelfth edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to George, Joel, Modestus, and J.W. for contributing to this issue.

Setting the Scene

The onchain economy has multiple narratives competing for attention. Tokenized real-world assets are reframing capital efficiency and collateral. Prediction markets are proving real consumer demand. Perpetual futures are building durable user bases.

While the new narratives stack up, one use case has quietly done the work for years: lending. It never depended on a viral moment to sustain itself. Lending maps cleanly to traditional credit markets: borrow against collateral, earn yield on idle assets. Lending survived DeFi summer, the NFT boom, and the memecoin supercycle. Every cycle crowns a new killer app, and lending is still there when the dust settles.

This issue reviews the lending sector through the lens of its leading protocols: Aave, Morpho, and Spark. The focus is on how each is performing now and what the data says about where the sector is heading. The issue closes with the CoinDesk Overnight Rate (CDOR), and how Dune's MCP made it possible to build a rate dashboard in minutes.

Aave

George | Website | Dashboard

Aave V4 reaches $134M total supplied with new incentives

New incentives launched a few weeks ago have accelerated Aave V4 growth. Around $8K in daily incentives attracted $40M of USDG and frxUSD deposits, which hit new deposit caps of $20M each within days. Growth extends beyond the incentivized stablecoins, with WETH, WBTC, weETH, and wstETH also driving meaningful inflows. Total supplied across V4 markets has tripled from $43M to $134M in the past month.

The incentives have placed V4 on a more level footing with other incentivized Aave V3 markets, and the recent inflows indicate that depositors are growing confident in the new V4 codebase. Yields on Aave V4 stand at 7.8% APY for USDG and 6.0% APY for frxUSD.

Morpho

Joel Obafemi | Website | Dashboard

Morpho captures 84% of Base lending TVL via $2.25B of cbBTC

Morpho holds 84% of Base lending TVL, up from 54% twelve months ago. The driver is Coinbase's cbBTC, designed for exactly this flow. $2.25B of cbBTC collateral on Morpho's Base markets backs $1.26B of stablecoin borrows, running at 56% utilization. Coinbase's stack and Morpho's design effectively function as one integrated product.

The same pattern holds across Morpho. Stablecoin lenders capture 96% of all borrow interest paid into the protocol, roughly $159M of $166M annualized. That interest is funded by $3.46B of BTC collateral sitting at 56% utilization protocol-wide, earning nothing for depositors because Morpho separates supply and collateral by design. Suppliers earn yield. Collateral holders do not.

Spark

Modestus Okoye | Website | Dashboard

SparkLend TVL grew 39%, but borrowers now fund only 31% of revenue

SparkLend is Sky’s lending market for DAI and USDS borrowing, but recent data shows a model growing less dependent on borrower demand. Over the last 90 days, TVL climbed 39%, from $2.38B to $3.31B, while utilization sits at 50%, down from a 64% peak in April 2025. That gap points to deposits outpacing borrower demand. For comparison, Fluid holds 99.6% utilization, Maple 94.3%, and Aave V3 78.1%.

The income statement makes the shift clearer. In May 2026, SparkLend earned more from a single PayPal yield account (44.8% of gross revenue) than from all borrower interest combined (30.7%). External yield deployments accounted for 68.6% of gross revenue. While Spark still presents as a lending market on the surface, its economics are now driven more by capital deployment than borrower demand.

CoinDesk Overnight Rate (CDOR)

J.W. | Website | Dashboard

The CDOR dashboard, built in one prompt

CDOR (CoinDesk Overnight Rate) is a daily benchmark interest rate series created by CoinDesk, built from activity in Aave's stablecoin lending pools. It converts the interest borrowers pay onchain into a standardized overnight rate. Because Aave's rates adjust dynamically with pool supply and demand, CDOR tracks how borrowers and lenders behave in real time. It is designed as DeFi's version of money-market benchmarks like SOFR, providing a foundation for interest rate derivatives and other rate-based products, but built purely from onchain activity.

Using Dune's Model Context Protocol (MCP), the CDOR dashboard came together in under ten minutes. The workflow was simple:

• Upload the methodology document

• Give a short instruction to apply the methodology and calculate the overnight rate

From there, the agent handled table discovery and query construction. What would typically take hours of digesting the methodology and writing SQL now fits into a single prompt.

Closing Thoughts

Lending has been a core pillar of the onchain economy since the beginning. Through multiple cycles, the lending market has been consolidating. A handful of major protocols are pulling share through battle-tested code and superior distribution, and the gap between these incumbents and the long tail of challengers is widening. The protocols that survive each cycle are the ones that compound these advantages, and that pattern is now visible in the numbers.

However, consolidation does not equal maturity. The sector still faces a massive capital efficiency problem: overcollateralization. Onchain lending remains overwhelmingly overcollateralized, which caps capital efficiency by design. Because borrowers must lock up more capital than they borrow, onchain lending stays a narrower version of traditional credit markets, where unsecured and undercollateralized credit play a far larger role. Until DeFi cracks this constraint, its ceiling stays fundamentally limited.

Solving the undercollateralized lending puzzle will require more than clever smart contracts. The foundation is being laid. How the sector closes the capital efficiency gap without reintroducing the systemic risks that overcollateralization was originally designed to prevent will be the defining narrative of the next credit cycle.

What We're Watching

• Mapping Contagion and Counterparties in the Sea of Tokens and Protocols

• Why Prediction Markets Matter

• The Asymmetric Cost of Money: Why the Consumer Yield Rail is Migrating Off-bank

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Visual Data Storyteller at Kalshi

• Senior Data Analyst at CertiK

• Data Governance and Management Lead at Anchorage Digital

Intro

In November 2025, Vitalik responded to an X post noting that Ethereum L1 fees had been negligible all year. His take was simple: just build on L1. He doubled down in February 2026, stating that Ethereum’s L2 scaling roadmap “no longer makes sense.” Both statements raise a question: is activity migrating back to Ethereum mainnet?

To answer that, this analysis examines three high-level metrics that capture the broadest view of network activity: revenue, transaction count, and total value secured (TVS). These are not the only metrics that matter, and other metrics such as DEX volumes or contract deployments may surface different patterns. But revenue, transactions, and TVS represent the foundational indicators that most market participants use to assess where activity lives. If migration were happening at any meaningful scale, it would show up there first.

Revenue: An Ecosystem-Wide Collapse

Ethereum mainnet revenue collapsed from $147M per month in January 2025 to $24M per month in April 2026. L2 revenue followed a similar trajectory, dropping from $22M per month to $6M per month over the same period. Both L1 and L2 fees compressed sharply in early 2025 and have remained at relatively low levels since.

However, revenue alone does not tell us whether usage migrated. Lower revenue can reflect lower fees, not necessarily lower activity. In this case, the decline appears to be driven primarily by a combination of weaker ETH prices, persistently low gas costs, and a broader cooling in speculative activity. Ethereum mainnet still generates materially more revenue than the combined L2 set, and the decline in fees is better understood as a market-wide compression than as evidence of a structural shift from L2s back to L1.

Transactions: Growth Without Migration

Transaction count gives a cleaner view of usage than revenue. On Ethereum mainnet, monthly transactions rose from 37M in early 2025 to 73M in April 2026, nearly doubling over 15 months. Combined L2 transactions stayed broadly stable in the 0.8B to 1.0B range over the same period.

There is, however, a notable distortion in the recent L2 data: the launch of MegaETH produced a temporary spike in L2 transaction counts that has since normalized. Excluding that, mainnet transaction count is growing while L2 transaction count has largely held steady. Even so, the aggregate L2 figure deserves scrutiny. New L2s continuously launch with incentive programs that attract bot activity and wash trading, inflating transaction counts before those chains fade to near-zero usage. The combined L2 number likely overstates organic activity.

The scale difference adds context. L2 transaction counts run in the hundreds of millions to billions per month, roughly 20x Ethereum mainnet. A gain of 30M monthly transactions is meaningful for mainnet. On the L2 side, that same volume is a rounding error. Mainnet’s transaction growth, while meaningful in isolation, does not constitute evidence of migration unless it is accompanied by a corresponding decline on the L2 side, which has not materialized.

TVS: L2s Are Holding Up, but Everything Is Down

Total value secured on both Ethereum mainnet and L2s rose through mid-2025 and has trended lower since. Ethereum reached $91B in August 2025, while L2s hit $53B in September 2025. Neither has returned to those levels.

Since January 2025, Ethereum mainnet TVS has declined from $66B to $45B, a decline of 31.9%. L2 TVS has dropped from $52B to $38B, or 26.9%, over the same period. The divergence is more noticeable in 2026: Ethereum is down 31.7% YTD, compared to “only” 11.4% for L2s.

These moves are still largely tied to ETH price. As ETH falls in dollar terms, so do dollar-denominated TVS figures. L2s have held up somewhat better than mainnet in percentage terms, but the broader trend is the same across both layers: both ecosystems are contracting in USD terms. That points to a market-wide drawdown rather than a reallocation of capital from L2s back to Ethereum mainnet.

The Bifurcation Inside L2s

The more interesting story is not between L1 and L2, but within L2s themselves. Among the top five L2s by TVL, only Base and Polygon have posted positive TVL growth YTD, at +2% and +6% respectively. Arbitrum is down 6%, Mantle is down 14%, and Optimism is down 28%.

The difference comes down to demand quality. The chains holding up have durable sources of activity that do not rely entirely on incentive cycles. Base benefits from Coinbase distribution, has no token, and has several major native applications including Aerodrome, Limitless, and Bankr. Polygon has Polymarket, which creates significant and persistent demand for blockspace. By contrast, the weaker chains have not built the same kind of structural moat. Arbitrum has the broadest app diversity but no dominant anchor application. Optimism onboarded EtherFi Cash in April 2026 and still posted a -28% TVL decline YTD.

This pattern also appears at the ecosystem level. GrowThePie tracks 97 live L2s above the $100K TVS threshold, down from 109 in June 2025. Many of these chains launched with incentive programs and now sit with near-zero activity. L2s are not losing users to Ethereum mainnet. Once incentive programs end, users simply move on to the next one.

Editor’s Note: GrowThePie tracks nearly 150 L2s in total. The figures above only include chains above the $100K TVS threshold. As ETH prices decline, some chains can fall below this cutoff without actually shutting down, so the true number of active L2s is likely higher than 97.

The (Lack of) Application Diversity

Application diversity is the clearest sign of L2 resilience. Ethereum mainnet hosts a broad mix of activity across lending, staking, DeFi, NFT infrastructure, and other categories. DeFiLlama tracks 1,863 protocols on Ethereum mainnet, followed by BSC (1,158), Arbitrum (1,117), and Base (948).

Among the top L2s, Arbitrum and Base are building toward broader diversification. The others are more concentrated. Polygon is heavily shaped by Polymarket, Optimism by EtherFi, and Mantle by Aave. That concentration can be a strength when the anchor application is growing. It can also be a weakness when the anchor slows, shifts chain strategy, or loses share.

Polymarket is the clearest example. On February 9, 2026, Polymarket demand pushed Polygon transaction costs higher than Ethereum mainnet’s, not because Polygon failed to scale, but because its blockspace was valuable enough that users were willing to pay a premium for it.

But concentration cuts both ways. When a chain’s activity depends primarily on one protocol, its trajectory becomes tied to that team’s decisions. If that application migrates to another chain, slows down, or pivots its product, the network’s metrics follow. Nexus explored this dynamic in a previous analysis of Polymarket within Polygon. Chains with diverse ecosystems can absorb those shocks more easily. Chains built around a single application inherit its risks.

Is the Migration Happening?

Across the three metrics examined, the data does not provide strong evidence of a broad migration from L2s back to Ethereum mainnet. Revenue and TVS are both down across L1 and L2s, driven by ETH price declines and fee compression rather than a structural shift in where users are transacting. Mainnet transaction count nearly doubled, which is notable, but without a corresponding decline on the L2 side, it is difficult to attribute that growth to migration rather than organic expansion.

What the data does reveal clearly is something more consequential: a consolidation within the L2 landscape itself. Activity is not flowing back to Ethereum mainnet. It is concentrating into the few L2s that built durable demand sources, while the rest fade after incentive programs end.

Vitalik’s recent comments should be read in that context. They were not a call for everyone to return to mainnet. They were a recognition that generic rollups serving only as cheap blockspace extensions may no longer be the right long-term answer. A recent Galaxy Research analysis of the Strawmap frames this as an explicit course correction away from the rollup-centric approach that defined the 2022–2025 cycle, with the direction now to scale the base layer, close the usage gap, and reduce dependency on L2s as the primary throughput solution.

The result is not a return to a pure L1 world. It is a pruning of the L2 stack. Most L2s are not losing users to Ethereum mainnet. They are losing relevance because they never developed enough independent demand to survive beyond the incentive cycle.

Methodology

The L2 data in the transaction count and TVS charts includes the following chains: Arbitrum One, Arbitrum Nova, Base, Celo, Fraxtal, Gravity, Ink, Linea, Loopring, Manta Pacific, Mantle, MegaETH, Metis, Mode Network, Optimism, Plume Network, Polygon, Ronin, Scroll, Soneium, Starknet, Taiko Alethia, Unichain, World Chain, and ZKsync Era.

What We're Watching

• What is HIP-4, and how do Hyperliquid’s outcome markets work?

• 10 Charts That Explain the RWA Boom

• Hyperliquid's non-crypto report by Allium

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Senior Data Engineer at Blockworks

• Senior Data Analyst at Bybit

• Quantitative Researcher at Monad Foundation

Intro

Welcome to the tenth edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to J.W. and Diego for contributing to this issue.

We would also like to acknowledge the opportunity to have contributed a small part to Pantera Capital’s State of Tokenization report, and this week’s edition highlights a few of the most interesting data points and our take on them.

Setting the Scene

Tokenization is clearly scaling, but most tokenized assets are still wrappers. Pantera Capital's State of Tokenization report quantifies what the market has been sensing: the industry is moving in the right direction, but it has not yet demonstrated that onchain representation fundamentally changes how those assets function.

That aligns with Nexus’s historical view: RWAs need to become more than simple representations of assets held offchain. Without active integration with DeFi, tokenized assets risk becoming little more than mirrored ledgers.

This week, Nexus unpacks Pantera Capital’s Tokenization Progress Index (TPI) and highlights a few of the data points that stood out in the report. For the full narrative and underlying methodology, see the full report on State of Tokenization.

Tokenization Progress Index (TPI)

The tokenized asset universe scores 2.04 out of 5 on onchain maturity

The Tokenization Progress Index (TPI) is Pantera Capital’s framework for measuring how far a tokenized asset has progressed onchain. It scores each asset across three dimensions, each rated from 1 to 5:

• Issuance & Redemption: how assets are minted and redeemed

• Transferability & Settlement: how assets transfer and settle

• Complexity & Composability: how assets can be deployed in smart contracts

The composite TPI score is the average of those three dimensions. Assets are then bucketed into three tiers:

• Wrappers: onchain representations of offchain claims (TPI of 2.5 or below)

• Hybrids: assets with partial onchain functionality (TPI above 2.5 and below 3.5)

• Natives: assets designed to operate primarily onchain (TPI of 3.5 or above)

Per Pantera Capital’s scoring, the market averages just 2.04 out of 5 across scored assets. Wrappers account for 77.6% of the universe, Hybrids 11.1%, and Natives only 2.7%. Of the three dimensions, Transferability & Settlement has progressed the furthest, with 44.3% of assets reaching a score of 3 or higher. Issuance & Redemption and Complexity & Composability both lag, with roughly 90% of scored assets remaining at scores of 1 or 2 in each dimension.

Transfer and settlement are the first dimension showing progress, while the other two still have significant ground to cover. For the market to move beyond wrappers, onchain transferability alone is not enough. The takeaway from the TPI data is clear: tokenization has proven that assets can be represented onchain, but it has not yet proven they can operate natively there.

Tokenization Market = Stablecoin Market

Stablecoins account for 91.6% of all tokenized assets

Stablecoins make up 91.6% of total tokenized market value. Every other asset class, including Treasuries, Commodities, and Private Credit, fits inside the remaining 8.4%. In other words, most tokenization growth charts are stablecoin charts in disguise at the moment.

The gap is not just about size. Stablecoins also have the highest average composite TPI at 2.67, ahead of every other asset class. Most other categories cluster around or below 2:

• Treasuries: 2.15

• Commodities: 1.93

• Private Credit: 2.01

• Real Estate: 1.27

Removing stablecoins reveals a much smaller and earlier market. Tokenized Treasuries at $12B and Commodities at $7B lead the remaining categories, but neither approaches the scale or maturity of stablecoins. Until other asset classes scale meaningfully, tokenization’s headline numbers will continue to be dominated by a single category.

Capital and Maturity: A Chicken-or-Egg Problem

Capital and maturity are moving together, but which leads is still unclear

At the asset-class level, the categories with the most capital onchain also tend to score higher on maturity. Stablecoins lead both dimensions at $293B and a TPI of 2.67. Treasuries follow at $12B and 2.15. Beyond that, market value generally declines alongside TPI.

Tokenized Stocks are a notable outlier at $960M and a TPI of 2.25, ahead of categories with significantly more capital. The underlying assets are simpler than other tokenized categories: high liquidity, real-time price feeds, and standardized settlement. That structural simplicity gives tokenized equities an advantage in onchain maturity.

Real Estate ($259M, TPI 1.27) and Private Equity ($486M, TPI 1.50) sit at the opposite end. Both rely on illiquid underlying assets, complex legal structures, and valuation processes that still run entirely offchain. Those characteristics make them the hardest categories to move beyond the wrapper phase.

Asset complexity appears to be related to tokenization maturity. Liquid, standardized assets tend to progress faster onchain, while more complex and illiquid categories lag. The market is beginning to reflect that pattern, but most asset classes still cluster in the lower-middle range of TPI.

There is a chicken-or-egg dynamic at play. Does higher onchain maturity attract capital, or does capital inflow fund the infrastructure that raises maturity? It is difficult to say which leads, but the data shows that scale and maturity are beginning to move in the same direction.

Private Credit Leads DeFi Utilization

64.3% of tokenized Private Credit is deployed in DeFi, compared to 9.0% for stablecoins

The most notable finding in the report is not about size. It is about utility. Of all tokenized Private Credit onchain, 64.3% is actively utilized in DeFi protocols. Stablecoins, despite being the largest category by far, sit at just 9.0%. On a utilization basis, Private Credit is the most onchain-active asset class in the tokenized universe.

That number comes with a caveat. Private Credit's DeFi usage is concentrated in a small number of products. Maple's syrupUSDT and syrupUSDC together account for approximately two-thirds of the category's active DeFi TVL. A similar concentration appears in Active Strategies, where 19% of the category's value is locked in DeFi, but Superstate's Crypto Carry Fund alone accounts for approximately 80% of that total.

Composability exists in both cases, but it has not yet broadened across the category. A small number of protocols are proving that tokenized assets can be productive onchain. When a tokenized asset is designed for DeFi composability, utilization follows. The challenge is extending that design pattern to more asset classes. Until that happens, composability will remain concentrated in the few categories and projects built for it.

Closing Thoughts

Tokenization is scaling. Maturity is not, at least not at the same pace. A TPI average of 2.04 out of 5 and a Wrapper share of 77.6% confirm that most tokenized assets now exist onchain in form, but not yet in function. That is an important first step, but it is not the final destination.

The market has proven that assets can be represented onchain. What it has not yet proven is that onchain representation changes how those assets actually work. Issuance remains gated, redemption routes through custodians, and composability is concentrated in stablecoins and a handful of private credit products. For most of the market, the token is moving onchain while the asset’s actual lifecycle remains anchored offchain. The market is heading in the right direction, but most of the work is still ahead.

Tokenization was never the endgame. Integrating those assets into the onchain economy is. The industry needs to move past replicating offchain products on a new ledger and start designing for what blockchains make uniquely possible. The tokenized market is still early. Whether it matures beyond the wrapper phase depends on whether the next wave of issuance is built for onchain utility, not just onchain presence.

What We're Watching

• The State of Prediction Markets

• Mapping the Strawmap: Ethereum’s Big Course Correction

• A Data-Driven Guide to Blockchain Infrastructure for TradFi Tokenization

• Mapping Contagion and Counterparties in the Sea of Tokens and Protocols

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Senior Data Analyst at Solana Foundation

• Data Scientist at Robinhood

• Data Analyst Director at Bybit

1. What Is the TOTAL2 Index?

Every crypto cycle has two stories: Bitcoin’s and everything else. TOTAL2 is the index that tracks the latter.

TOTAL2 tracks the combined market cap of the top 125 cryptocurrencies excluding Bitcoin. It covers the full breadth of the non-Bitcoin crypto market: Ethereum, Solana, layer 2s, DeFi protocols, and every other asset competing for capital outside of Bitcoin.

The formula is simple: take the combined market cap of the top 125 crypto assets and subtract Bitcoin’s market cap.

TOTAL2 = Top 125 Crypto Assets Market Cap − Bitcoin Market Cap

Like OTHERS, TOTAL2 is denominated in dollars, not as a percentage. It measures the total capital allocated to non-Bitcoin crypto assets at any given moment. When TOTAL2 rises, the combined market cap of non-Bitcoin crypto assets is growing, and vice versa. Where BTC Dominance shows whether capital is concentrated in Bitcoin specifically, TOTAL2 shows the full picture of what is happening everywhere else.

It is worth clarifying the difference between TOTAL2 and OTHERS, as the two indices are related but measure different segments of the market. TOTAL2 covers all non-Bitcoin assets in the top 125, including Ethereum and the rest of the top 10. OTHERS excludes the top 10 assets entirely. In other words, OTHERS is a subset of TOTAL2, not the other way around.

2. Why Does the TOTAL2 Index Move?

Risk appetite and market sentiment. TOTAL2 grows when investors are willing to deploy capital beyond Bitcoin. When risk appetite is high, capital flows into Ethereum and the broader altcoin market, pushing TOTAL2 higher in dollar terms. When fear takes over, altcoin exposure is reduced and TOTAL2 contracts.

Altcoin innovation cycles. Every cycle produces a new theme that pulls capital into the broader altcoin market. DeFi in 2020, NFTs in 2021, AI tokens in 2024. Each wave expanded TOTAL2 as money chased the latest narrative.

Ethereum as the anchor. Ethereum is the largest single component of TOTAL2 by a significant margin. Its price performance has an outsized effect on the index. When Ethereum appreciates, it tends to lift the broader index. When it sells off, it can weigh on TOTAL2 even when other assets are holding up.

Stablecoin distortion. TOTAL2 includes stablecoins like USDT and USDC, which now collectively exceed . Stablecoin accumulation can inflate the index even when there is no genuine shift in investor appetite for altcoins.

3. TOTAL2 Across Market Cycles

TOTAL2 has expanded and contracted across every major crypto cycle, but the drivers behind each move have been different.

2017 ICO boom. TOTAL2 surged from under $1B in early 2017 to over $400B at its January 2018 peak as the ICO wave flooded capital into thousands of new tokens. The collapse was equally swift, with TOTAL2 losing 90% of its value by late 2018.

2021 altcoin supercycle. TOTAL2 reached its all-time high in late 2021, peaking at approximately $1.6T as DeFi protocols, NFTs, and alternative layer 1s attracted capital across the entire crypto market. Ethereum led the move, but participation across the altcoin market was broader than any previous cycle.

2024 memecoin and AI rotation. Memecoins and AI tokens drove a sharp expansion in TOTAL2 even as Bitcoin set new highs on its own track. The broader altcoin market moved primarily on narrative momentum in this cycle. Capital chased themes, not infrastructure.

2024 to 2025 institutional era. The pattern shifted. Spot Bitcoin ETF inflows concentrated capital in Bitcoin through 2024, with Ethereum ETF flows gaining momentum later in 2025. Institutional capital entered crypto through regulated products that favored the two largest assets. The broader altcoin market did not benefit proportionally.

4. How to Read the TOTAL2 Index

TOTAL2 is often paired with Bitcoin's price to understand where capital is flowing across the crypto market.

5. Trading the TOTAL2 Index

TOTAL2 gives traders a way to express a directional view on the entire altcoin market without assembling individual positions. The strategies below are setups commonly used to trade broad altcoin exposure. They are included here for educational purposes only. None of this is financial advice. Always do your own research before making any trading decisions.

Altseason Positioning

TOTAL2 tends to expand most aggressively when capital rotates broadly out of Bitcoin and into the altcoin market. Historically, this rotation follows a period of Bitcoin strength, where BTC Dominance peaks and begins to roll over, signaling that capital is starting to move down the risk curve.

How traders approach it: Monitor BTC Dominance for signs of a peak and rollover. When dominance begins declining from an extended high, go long TOTAL2 as the rotation signal confirms. Reduce exposure or exit when BTC Dominance starts recovering.

Relative Strength: TOTAL2/BTC Ratio

The TOTAL2/BTC ratio strips out the overall direction of the crypto market and isolates one question: is the broader altcoin market gaining or losing ground against Bitcoin? When the ratio breaks out of a sustained base, capital is rotating into altcoins. When it breaks down, altcoins are losing ground relative to Bitcoin.

How traders approach it: Watch the TOTAL2/BTC ratio chart. When the ratio starts climbing after a long flat period, capital is rotating into the broader altcoin market. Go long TOTAL2. When the ratio starts dropping after a sustained uptrend, altcoins are losing ground. Short TOTAL2 or reduce exposure.

6. Trading the TOTAL2 Index Onchain

Historically, expressing a view on the broader altcoin market meant assembling a portfolio of individual tokens, managing different risk profiles, and constantly rebalancing as narratives shifted. The position rarely reflected the original thesis cleanly.

Paragon (@tradeparagon) addresses this directly. It offers a TOTAL2 perpetual contract on Hyperliquid, giving traders direct exposure to the entire altcoin market excluding Bitcoin through a single position.

Beyond TOTAL2, Paragon also lists BTC.D, which measures Bitcoin’s share of the total crypto market, and OTHERS, which tracks the long tail of the market excluding the top 10. Together, the three indices cover the major segments of crypto market structure.

Learn more at Paragon.

Disclaimer

This article was produced in partnership with Paragon. The content is for informational and educational purposes only and does not constitute financial, investment, or trading advice. Nothing in this article should be relied on as a recommendation to buy, sell, or hold any digital asset. Do your own research before making any trading decisions.

By Diego Cabral

The article is also available on X.

Setting the Scene

One of the fastest-growing sectors of the onchain economy remains largely invisible in mainstream analysis: non-USD stablecoins.

This report breaks down local currency stablecoins, analyzing their metrics, defining how the sector fits into the broader stablecoin landscape, mapping the opportunity, and presenting the data in a way that makes what comes next measurable.

The Problem: Onchain Is a Dollar World. The Real World Isn't.

The stablecoin market is one of crypto’s clearest product-market fits, with total supply of $298B. Yet a structural imbalance sits beneath that number. In traditional foreign exchange markets, the US dollar is involved in roughly 89% of all transactions (BIS Triennial Survey, April 2025). In the onchain economy, the concentration is far more extreme: non-USD stablecoins represent just 0.4% of total stablecoin supply.

The gap between how the world transacts and how the onchain economy is structured remains largely unaddressed.

Why Does This Gap Exist?

The stablecoin market was built by and for crypto-native users. Tether launched in 2014 to solve a specific problem: giving traders dollar liquidity without leaving crypto exchanges. That use case defined the entire category, and dollar-pegged stablecoins became the default unit of account, collateral, and settlement across the onchain economy.

For users with stable access to dollar financial services, this works. For the majority of the world, where salaries, taxes, rent, and business expenses are denominated in local currencies, it introduces unwanted FX risk.

Local currency stablecoins move value onchain 24/7, borderless and programmable, while staying denominated in the currency the user actually transacts in.

Non-USD stablecoins are not competing with USDT or USDC. They are completing the onchain economy's infrastructure by serving the part of the global monetary stack that dollar stablecoins, by design, were never built to reach.

Why Now?

There is already clear data showing sustained demand for non-USD stablecoins. Over the past three years, the market cap of local currency stablecoins has grown roughly 3.54x, from $379M to $1.34B.

EURC accounts for the majority of that growth and remains the dominant non-USD stablecoin by both supply and volume. But growth has not been limited to a single asset or region. Brazilian real, Swiss franc, Japanese yen, and Singapore dollar stablecoins have all expanded in supply, each responding to local demand rather than a single macro catalyst. Three forces are driving this expansion: regulatory frameworks, a largely untapped addressable market, and a shifting competitive landscape.

The Regulatory Catalyst

The strongest structural driver of this growth has been regulatory clarity.

• Circle’s EURC became the first MiCA-licensed euro stablecoin in July 2024. Post-MiCA, EURC volumes increased 1,139% and Societe Generale’s EURCV volumes rose 343%. Building on that momentum, a consortium of 12 European banks, including ING, UniCredit, BNP Paribas, and BBVA, formed Qivalis to launch a MiCA-compliant euro stablecoin in H2 2026.

• Japan’s JPYC launched as the country’s first regulated yen-backed stablecoin in October 2025, registered under Japan’s Financial Services Agency.

• South Korea saw KRW1 launch on Avalanche in September 2025 and KRWQ debut on Coinbase’s Base in October 2025. KakaoBank advanced its won-pegged stablecoin preparations ahead of pending legislation.

The pattern is clear: a wave of sovereign stablecoin issuance, with each jurisdiction effectively betting that its currency deserves a position in the onchain economy.

Market Size: The Opportunity in Context

The addressable market for non-USD stablecoins is significant regardless of how it is framed. Global M2 outside the United States is estimated around $100T, meaning even 1% stablecoin penetration implies an $800B to $1T opportunity.

Cross-border payment flows reached approximately $208T in 2025, projected to exceed $320T by 2032. B2B payments alone account for more than $34T annually. Remittance costs still average around 6.5%, largely driven by FX spreads and correspondent banking fees. These are the frictions that local currency stablecoins directly reduce.

Total non-USD stablecoin supply currently sits at approximately $1.29B, or 0.4% of the total stablecoin market. The gap between current supply and the implied opportunity speaks for itself. The constraint is not demand. It is infrastructure maturity, regulatory clarity, and distribution, and all three are progressing.

Current Market: The Dollar Network Effect

The primary competitor to non-USD stablecoins is the entrenched position of USD-denominated assets across every layer of the onchain economy.

USDT and USDC dominate liquidity on every major chain, DEX, and CEX. Most DeFi protocols are built around dollar-denominated collateral. Most traders price in dollars. Most crypto-native users hold dollars as their base asset.

This network effect is the single largest structural barrier to non-USD stablecoin adoption. Even users in countries with strong local currencies often default to USD stablecoins simply because liquidity is more readily available and integrations are established.

The implication: non-USD stablecoins will not win by competing with USDT or USDC head-on. They will win by serving the use cases where dollar denomination creates friction: domestic treasury operations, local payment rails, and regional B2B settlement. In these contexts, local currency is not a preference but a necessity.

The Protocols: Who Is Building

• EURC is the largest non-USD stablecoin by supply and transfer volume. Issued by Circle, fully reserved, and MiCA-compliant, it has emerged as the dominant digital euro.

• Frankencoin (ZCHF) is the largest CHF stablecoin onchain, pegged 1:1 to the Swiss franc. ZCHF's market cap reached $38M while average wallet balance declined from roughly $90K to under $25K.

• BRZ by Transfero is the largest BRL-pegged stablecoin onchain, with $445M in circulating supply and over 8,600 holders.

Closing Thoughts

The structural gap between real-world FX and onchain is not permanent. It is a byproduct of how the stablecoin market was built, and the data indicates the gap is beginning to narrow.

The evidence over the past three years is consistent. The question is no longer whether this gap closes, but at what pace, and which protocols capture the most value in the process.

The non-USD stablecoin dashboard built in partnership with Token Terminal is designed to track this in real time, across every major non-USD stablecoin, with the full stack of onchain metrics that matter. The dashboard is a work in progress, and we welcome feedback as we continue to refine it. The opportunity is measured in trillions. The infrastructure to capture it is just getting started.

By Diego Cabral

The article is also available on X.

Introduction

John Bogle, founder of Vanguard, once said:

“Don’t look for the needle in the haystack. Just buy the haystack.”

That idea built Vanguard into a $10 trillion firm and changed how a generation invests. Crypto, for all its innovation, never had an equivalent. Until now.

If you have followed crypto markets, you already know these scenarios:

• BTC dominance ticking up while altcoins bleed

• The rest of the market catching up while BTC goes sideways

• Altcoins lagging while ETH and SOL lead the move

You tracked them, formed a view, and then spent the next hour assembling a basket of tokens, rebalancing as prices moved, and ending up with a position that only loosely reflected the original thesis you started with.

The problem was never the view. The instrument simply did not exist.

That’s the gap Paragon is trying to bridge.

What Is Paragon?

Paragon is a trading platform that turns crypto market indices into tradeable perpetual contracts, built natively on Hyperliquid. The same benchmarks tracked on TradingView are now tradeable as perpetuals:

• BTC.D: Bitcoin’s dominance

• TOTAL2: Total altcoin market cap

• OTHERS: Total market cap excluding the top 10 assets

All three are now tradeable as single positions. No baskets. No rebalancing.

Paragon runs natively on Hyperliquid, using USDC collateral, standard order types, low latency, and onchain settlement.

The Three Available Markets

BTC.D measures Bitcoin's share of the total crypto market. It indicates whether capital is concentrated in Bitcoin or spread across the broader market.

TOTAL2 tracks the total crypto market cap excluding Bitcoin. It captures whether capital is flowing into the broader altcoin market.

OTHERS covers the total crypto market cap excluding the top 10 assets. It shows whether capital is reaching the small and mid-cap end of the market.

More markets are in development. These three markets cover the most important macro views in crypto.

Why This Actually Matters

Before Paragon, expressing a view on BTC Dominance meant building a multi-leg position across multiple assets, constantly adjusting as prices moved. The exposure was always imperfect, and the rebalancing was endless. There was no clean way to express the view.

Now that exact view fits into one position. Long BTC.D. That is it.

The same logic applies to hedging. For anyone holding a portfolio of altcoins and concerned about downside, shorting TOTAL2 provides index-level protection against a broad altcoin drawdown without liquidating existing positions.

One position. Clean exposure.

How to Start Trading

Step 1: Go to app.hyperliquid.xyz

Paragon markets are live on Hyperliquid's native trading interface. For anyone already on Hyperliquid, no additional setup is required.

Step 2: Search for the market

In the Hyperliquid search bar, type BTC.D, TOTAL2, or OTHERS. Paragon markets appear with the para: prefix (e.g. para:OTHERS)

Step 3: Connect your wallet

Click Connect in the top right corner and log in with an email or a compatible wallet such as Rabby or MetaMask. If funds are already on Hyperliquid, trading is available immediately. If not, click the deposit button in the top menu, select the asset and network, and transfer funds before placing a trade.

Step 4: Choose direction and size

Decide whether to go long (the index is expected to rise) or short (the index is expected to fall). Enter the position size in the trading panel on the right side of the screen. Max leverage is 50x, but keeping it low is the right call for beginners. These indices can move quickly during macro shifts.

Collateral is USDC, and there is no expiry date. The position stays open until it is closed.

Step 5: Pick an order type

• Market order. Executes immediately at the current price. Fast, but takes whatever spread exists at that moment.

• Limit order. Set a specific entry price. Better for precision.

• Stop order. Closes the position automatically if the index moves against it.

A limit order near the current price is the cleanest way to enter for most people starting out.

Step 6: Confirm and monitor

Once the order fills, it appears in the positions panel. Funding is paid hourly, standard Hyperliquid mechanics, so keep an eye on that cost when holding for extended periods. Open orders and positions can be managed at any time in the panel below the main chart.

A Few Ways to Use Paragon

• Alt season thesis: Long TOTAL2 when the broader altcoin market is showing signs of momentum without having to pick individual tokens.

• Bitcoin dominance play: Long BTC.D when the market is favoring Bitcoin over the broader altcoin market.

• Portfolio hedge: Short OTHERS to protect a small-cap portfolio against a broad market drawdown without liquidating existing positions.

• Relative value: Long BTC.D and short BTC simultaneously to express a pure dominance view, isolating the signal from Bitcoin's price direction entirely.

Bottom Line

Paragon is the first venue that makes the crypto macro view directly tradeable. BTC Dominance, the broader altcoin market, and the long tail of small caps are the frameworks traders rely on to navigate crypto cycles. Until now, acting on those views required assembling multiple positions, managing constant rebalancing, and accepting imperfect exposure.

Paragon collapses that into a single instrument. The view is the position.

Learn more at Paragon.trade

Disclaimer

This article was produced in partnership with Paragon. The content is for informational and educational purposes only and does not constitute financial, investment, or trading advice. Nothing in this article should be relied on as a recommendation to buy, sell, or hold any digital asset. Do your own research before making any trading decisions.

Intro

Welcome to the ninth edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to Elton, Borja, and Diego for contributing to this issue.

Setting the Scene

The yield-bearing stablecoin market has grown over 7,000% since January 2024, from under $1B to over $22B. As the Fed Funds Rate declined from 5.3% to 4.3%, capital is searching for onchain yield alternatives beyond pure T-bill wrappers. Despite rates continuing to decline, yield-bearing stablecoin supply has continued to grow, suggesting the demand goes beyond rate sensitivity.

But that growth was not evenly distributed. sUSDS leads at $7.1B market cap, accounting for 32% of the category. sUSDe follows at $4.4B. Below them, a competitive layer is forming. USYC, SyrupUSDC, BUIDL, and USDY each compete on backing structure, chain distribution, and yield source.

What separates them is how the yield is generated. Treasury exposure, delta-neutral strategies, private credit, and home equity lines all carry the yield-bearing label, but each comes with a fundamentally different risk profile.

Building on last week's coverage of yield-bearing tokens, this edition covers two more: PRIME, and SyrupUSDC. Each takes a distinct approach to generating yield onchain.

PRIME by Figure

Borja Neira | Website | Dashboard

PRIME reaches $327M after its launch in December 2025

PRIME is a yield-bearing token representing tokenized exposure to US home equity lines of credit (HELOCs) originated by Figure Technologies. Figure and its partners have originated over $19B of home equity to date, making the ecosystem the largest non-bank provider of home equity financing. The asset is concentrated entirely on Solana, distributed through Kamino.

PRIME reached $327M as of April 2026, four months after its December 2025 launch. Growth was front-loaded, crossing $300M within 75 days before consolidating in a $300M to $360M range. Supply peaked at $364M in early April before retracing 10%.

Tokenized home equity credit is a novel use case for DeFi. How PRIME performs through a housing market downturn or a sustained period of rising rates will be the real test of this model.

SyrupUSDC by Maple

Diego Cabral | Website | Dashboard

SyrupUSDC market cap grew from $52M to $1.63B in 14 months as Solana leads DeFi utilization

SyrupUSDC is Maple's yield-bearing stablecoin, backed by institutional private credit rather than money markets or T-bills. Since February 2025, market cap grew from $52M to $1.63B across Ethereum, Solana, Base, and Arbitrum (+3,049%), making it the fourth largest yield-bearing stablecoin on Ethereum behind sUSDS, sUSDe, and USYC.

Ethereum holds 87% of total supply, but only accounts for 36% of SyrupUSDC deployed in DeFi. Solana tells a different story. Despite holding just 13% of total onchain supply, it accounts for 54% of DeFi utilization. Of the $289M actively deployed in DeFi, Solana leads with $156M, followed by Ethereum at $105M, Base at $19M, and Arbitrum at $9M.

Closing Thoughts

Yield-bearing tokens share a common label, but that label can be deceiving. The underlying risk profiles vary significantly. PRIME draws yield from US home equity credit, while SyrupUSDC taps institutional private credit.

The category is scaling, and so are the risks that come with it. Home equity credit faces housing market cyclicality. Institutional private credit depends on sustained borrower demand and credit quality. How each model performs under stress will separate durable yield from temporary incentives. Sustainability, not scale, will determine which tokens survive.

What We're Watching

• Maple Finance Status Update

• The Hitchhiker’s Guide to Onchain Credit

• DeFiLlama SQL Studio

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Senior Data Engineer at Polymarket

• Senior Data Engineer at Keyrock

• Senior Data Scientist at OKX

1. What Is the OTHERS Index?

The top 10 crypto assets tend to dominate major headlines and drive most of the market cap. But the long tail of mid and small caps beyond them tells a different story.

OTHERS tracks the combined market cap of the top 125 crypto assets outside the top 10. It covers the long tail of the market: small caps, mid caps, memecoins, alternative Layer 1s, AI tokens, and other smaller names that collectively move billions of dollars.

The math is straightforward: take the combined market cap of the top 125 crypto assets and subtract the top 10.

OTHERS = Top 125 Crypto Assets Market Cap − Top 10 Crypto Assets Market Cap

Unlike BTC Dominance, OTHERS is denominated in dollars, not as a percentage. It measures how much capital is allocated to the long tail at any given moment. Where BTC Dominance shows whether capital is concentrated in Bitcoin, OTHERS shows whether it is reaching the riskiest part of the market, the part that historically moves last and moves fastest.

2. Why Does the OTHERS Index Move?

OTHERS is driven by dynamics that play out differently from Bitcoin and the majors.

Risk appetite at its extreme. Small caps sit at the far end of the risk curve. OTHERS expands when speculation is running hot and traders start reaching further down the curve beyond the major cryptocurrencies in search of higher returns.

Narrative-driven rotations. The long tail is where new themes are born. AI tokens, memecoins, RWA tokens, DePIN. Each new narrative spawns dozens or hundreds of small projects. When a theme catches fire, capital flows into the OTHERS bucket faster than it does into Bitcoin or established large caps.

Liquidity conditions. Small caps need loose money to thrive. When there is plenty of money flowing through the market, capital reaches further down the risk curve and OTHERS expands. When money tightens and investors turn cautious, the long tail bleeds first. Traders sell their riskiest positions before anything else.

3. OTHERS Across Market Cycles

OTHERS has expanded during every major altcoin cycle, but the trigger has been different each time.

2017 ICO boom. OTHERS had its first real moment. The ICO wave produced thousands of new tokens, most sitting well outside the top 10. The index expanded from under $1 billion in early 2017 to roughly $68 billion at its January 2018 peak. When the bubble collapsed, it gave back nearly all of those gains.

2021 altcoin supercycle. OTHERS reached its all-time high in late 2021 as DeFi protocols, NFTs, and alternative Layer 1s pulled capital deep into the long tail. The index peaked at roughly $415 billion, more than five times its 2018 high. It was the broadest capital rotation the long tail had seen to that point.

2024 memecoin and AI rotation. In the earlier part of the cycle, memecoins on Solana and Base and AI tokens drove a sharp expansion in OTHERS even as Bitcoin set new highs on its own track. For the first time, the long tail moved primarily on narrative momentum rather than infrastructure buildouts.

2024 institutional era. As the cycle matured, the historical pattern broke. ETF inflows and corporate treasury purchases concentrated capital in Bitcoin, with secondary flows into Ethereum. The long tail did not benefit proportionally from the bull market. OTHERS lagged the majors, marking a structural shift in how capital enters crypto.

4. How to Read the OTHERS Index

OTHERS is often paired with Bitcoin's price to understand whether capital is flowing all the way down to the long tail or staying concentrated in the majors.

5. Trading the OTHERS Index

OTHERS gives traders a way to take a directional view on the small-cap segment of the market without assembling dozens of individual positions. The strategies below are setups commonly used to express views on altcoin indices. They are included here for educational purposes only. None of this is financial advice. Always do your own research before making any trading decisions.

Trend Setup: 50-Day and 200-Day Moving Average Cross

The 50-day and 200-day moving averages are used to define the broader trend for OTHERS. When the 50-day SMA crosses above the 200-day SMA on the weekly chart, historically known as a golden cross, it has marked the start of multi-quarter expansions in the long tail. The inverse cross has signaled prolonged contractions.

How traders approach it: go long OTHERS on a confirmed weekly close after the 50-day SMA crosses above the 200-day SMA on the weekly chart. Exit or short on the reverse cross.

Relative Strength: OTHERS / BTC Ratio

The OTHERS/BTC ratio strips out the overall direction of crypto and isolates one question: is the long tail gaining or losing ground against Bitcoin? When the ratio breaks out of a sustained base, capital is starting to favor small caps. When it breaks down, the long tail is losing ground relative to the safest crypto holding.

How traders approach it: watch the OTHERS/BTC ratio chart. When the ratio starts climbing after a long flat period, capital is rotating into small caps. Go long OTHERS. When the ratio starts dropping after a sustained uptrend, the long tail is losing ground relative to Bitcoin. Short OTHERS.

Cycle Positioning: Late Bull Long, Early Bear Short

OTHERS has never led a cycle. It lags. Bitcoin moves first, then capital flows into Ethereum and the rest of the top 10, and only after that does it reach the long tail. In bear markets, the reverse is also true. Small caps bleed first because investors exit their riskiest positions before anything else.

How traders approach it: go long OTHERS once BTC Dominance has rolled over from a peak and total crypto market cap is printing new highs. Reduce exposure or short OTHERS at the first signs of broader market weakness, as the long tail tends to sell off before the majors.

6. Trading the OTHERS Index Onchain

Until now, getting concentrated exposure to the small-cap segment of the crypto market meant assembling and rebalancing a basket of dozens of individual tokens. Gas fees, slippage on illiquid pairs, and projects rotating in and out of relevance added up quickly. The position traders ended up with rarely reflected the original thesis.

Paragon (@tradeparagon) addresses this directly. It lists an OTHERS perpetual contract on Hyperliquid, letting traders express a view on the entire long tail of the market through a single instrument without managing multiple positions.

Beyond OTHERS, Paragon also lists BTC.D, which measures Bitcoin’s share of the total crypto market, and TOTAL2, which tracks the altcoin market excluding Bitcoin. Together, the three indices cover the major segments of crypto market structure, whether that is hedging an altcoin portfolio, positioning for rotation between majors and small caps, or trading the long tail as a standalone market.

Learn more at Paragon.

Disclaimer

This article was produced in partnership with Paragon. The content is for informational and educational purposes only and does not constitute financial, investment, or trading advice. Nothing in this article should be relied on as a recommendation to buy, sell, or hold any digital asset. Do your own research before making any trading decisions.

1. What Is BTC Dominance (BTC.D)?

Picture the entire crypto market as a pie. Every coin, token, and digital asset takes a slice. BTC Dominance (BTC.D) measures how large Bitcoin’s slice is relative to the whole pie.

The math is straightforward: take Bitcoin’s market cap, divide it by the combined market cap of the top 125 crypto assets, and express it as a percentage.

BTC Dominance = (Bitcoin Market Cap ÷ Top 125 Crypto Assets Market Cap)

Think of it this way: if the entire crypto market is worth $3 trillion and Bitcoin accounts for $1.8 trillion of that, BTC.D is 60%.

In simple terms, BTC.D tells you where capital is concentrated. When BTC.D is high, above 60%, most of the money in crypto is sitting in Bitcoin. When it drops toward 40% or lower, that capital is spreading into altcoins. BTC.D does not tell you whether Bitcoin’s price is going up or down. It tells you where investors are choosing to allocate their money in the crypto market.

While the formula is simple, it reveals far more than the math suggests. BTC.D acts as a real-time indicator of market sentiment, showing whether the market is consolidating around Bitcoin or expanding into riskier assets.

2. Why Does BTC Dominance Move?

BTC.D shifts when the balance between Bitcoin and the rest of the market changes.

Market sentiment and risk appetite. When traders are willing to take on risk, capital rotates out of Bitcoin into smaller, more volatile assets in search of higher returns. This pushes BTC.D lower. When fear takes over, the opposite happens. Capital consolidates back into Bitcoin.

Altcoin innovation cycles. New narratives consistently pull capital away from Bitcoin. DeFi Summer in 2020, NFTs in 2021, and AI tokens in 2024 each triggered sharp drops in dominance as money rotated into the latest theme. Bitcoin did not necessarily fall in price; it simply grew more slowly than the rest of the market.

Institutional adoption. Large institutions mostly buy Bitcoin, not altcoins. The approval of spot Bitcoin ETFs in January 2024 marked a structural shift. Billions flowed into BTC through regulated products, pushing BTC.D from 52% in early 2024 to over 58% within a year, as institutional inflows concentrated specifically in Bitcoin rather than spreading across the market.

Stablecoin distortion. Stablecoins like USDT and USDC are included in the total market cap calculation. With stablecoins now accounting for over $300B of the total crypto market, their growth can push BTC.D lower even when nothing has actually changed in how investors feel about Bitcoin versus altcoins. This is worth keeping in mind when dominance moves without an obvious reason.

3. BTC Dominance Across Market Cycles

BTC.D follows recognizable patterns across bull and bear markets. Here is what history shows:

2017 ICO boom. BTC.D collapsed from ~95% to ~39% as thousands of new tokens launched and absorbed capital. Bitcoin was hitting all-time highs in dollar terms, but everything else was growing faster.

2018 bear market. When the bubble burst, altcoins fell harder than Bitcoin. Investors retreated to BTC as the least-bad option, and dominance climbed back toward 70% by late 2019.

2020 DeFi and NFT bull market. BTC.D dropped from ~70% in January 2021 to ~40% by May 2021 as DeFi protocols, NFTs, and alternative Layer 1 blockchains pulled massive capital away from Bitcoin.

2022 LUNA and FTX collapses. Two of the biggest failures in crypto history triggered panic across the market. Even as everything fell, Bitcoin fell less. BTC.D climbed from ~40% to ~47% as traders parked in Bitcoin relative to everything else.

2024 institutional era. ETF inflows and corporate Bitcoin treasury purchases pushed BTC.D back above 65%. Unlike previous cycles, dominance rose during a bull market, driven by institutional money that specifically favored Bitcoin.

4. How to Read BTC Dominance

BTC.D is most useful when read alongside Bitcoin’s price. Together, the two tell you how capital is actually moving across the market:

5. Trading BTC Dominance

BTC.D can be traded as a direct expression of where the market is headed. The setups below are strategies traders have historically used to position around dominance shifts. They are included here for educational purposes only. None of this is financial advice. Always do your own research before making any trading decisions.

Altseason Signal (BTC.D below 54%)

When BTC.D closes below 54% on the weekly chart, it has historically signaled that capital is starting to rotate into altcoins.

How traders approach it: wait for a confirmed weekly close below 54%, then short BTC.D, betting that dominance will continue to fall as altcoins pick up momentum.

BTC Strength Signal (BTC.D above 60%)

When BTC.D pushes above 60%, it has historically meant Bitcoin is outperforming the broader market. Institutional buyers tend to favor BTC at these levels, and the trend can persist.

How traders approach it: wait for a confirmed weekly close above 60%, then go long BTC.D, betting that Bitcoin continues to outperform.

100-Week Moving Average Rejection

The 100-week moving average represents the average of BTC.D’s weekly closes over the past two years. Think of it as the market’s baseline for normal dominance.

When BTC.D rallies back to that level from below and fails to break through, traders interpret it as a sign that the move is losing strength, and dominance is likely to fall again.

How traders approach it: monitor the 100-week SMA on the BTC.D chart, wait for BTC.D to tag the line and fail to break above it, then short BTC.D, expecting a move lower.

6. Trading BTC Dominance Onchain

Historically, taking a position on BTC Dominance required managing multiple trades at once. Traders would long Bitcoin and short a basket of altcoins, then constantly rebalance as prices moved. It was messy and expensive, and introduced execution complexity and rebalancing risk that made the final position a rough approximation of the original thesis at best.

Paragon (@tradeparagon) was built to solve that. It offers a BTC Dominance perpetual contract on Hyperliquid, giving traders direct exposure to BTC.D in a single position.

Beyond BTC.D, Paragon offers two additional index perpetuals: OTHERS, tracking the total crypto market cap excluding the top 10 assets, and TOTAL2, covering the broader altcoin market excluding Bitcoin. Together, the three products give traders a toolkit for expressing macro views on crypto market structure, whether that is hedging an altcoin portfolio, positioning for rotation, or trading dominance as its own market.

Learn more at Paragon.

Disclaimer

This article was produced in partnership with Paragon. The content is for informational and educational purposes only and does not constitute financial, investment, or trading advice. Nothing in this article should be relied on as a recommendation to buy, sell, or hold any digital asset. Do your own research before making any trading decisions.

Intro

Welcome to the eighth edition of Nexus Data Labs. We are here to tell stories about onchain data. Our aim is to alert you to what really matters in the fast-developing world of onchain finance.

Thank you to Borja and Tom for contributing to this issue.

Setting the Scene

Yield-bearing tokens have drawn increasing attention across DeFi. As onchain treasuries and DAOs grow, so does the need to deploy idle capital productively. Holding stablecoins without yield is an opportunity cost that protocol treasuries can no longer justify at scale.

But yield alone is not enough. The source of that yield matters. A token backed by short-term US Treasuries carries a fundamentally different risk profile than one backed by perpetual futures funding rates or private credit. The convergence between TradFi yield sources and onchain distribution is no longer theoretical. It is happening at scale, with money market funds, government securities, and institutional lending all serving as backing for tokens that sit natively in DeFi.

The question is no longer whether yield should be tokenized, but which structures generate it, where the risk actually sits, and who captures the return.

This week, we break down three yield-bearing tokens: USYC, sUSDe, and BUIDL. Each takes a distinct approach to generating yield onchain.

USYC by Circle

Borja Neira | Website | Dashboard

USYC surges to $2.9B with 96% of supply concentrated on BNB Chain

USYC is a tokenized money market fund issued by Hashnote, a Circle subsidiary, backed by short-term US Treasury bills and reverse repo agreements. As of April 2026, USYC reached $2.90B in AUM, up 460% YoY and 91% YTD, overtaking BUIDL to become the largest tokenized Treasury product.

The growth is concentrated on a single chain and a single use case. 96% of supply ($2.79B) sits on BNB Chain as off-exchange collateral for Binance’s institutional derivatives business since its launch in July 2025. Ethereum supply, which peaked at $1.68B in January 2025, has since compressed to $110M.

sUSDe by Ethena

Tom Wan | Website | Dashboard

sUSDe staking ratio climbs to 60% as Ethena diversifies beyond funding rates

USDe is Ethena’s synthetic dollar, primarily backed by a delta-neutral strategy that pairs long spot positions in ETH and BTC with corresponding short perpetual futures to generate yield for sUSDe holders (Staked version of USDe).

While staked USDe supply has contracted from its $14B peak, the staking ratio climbed from 39% to 60%. Holders are increasingly locking up USDe for yield rather than holding it idle.

Yield has been modest, sitting in the 3.3-5.5% APY range since October 2025 as Q1 2026 average crypto perp funding fell to 1.74%. Ethena has been diversifying away from pure funding rate dependence by building USDtb to capture T-bill yield, but a prolonged bear market still makes sUSDe uncompetitive against direct T-bill rates and yield-bearing stablecoin alternatives like sUSDS.

A recent proposal from the Ethena Risk Committee expands yield sources to CeFi institutional lending, liquid RWAs beyond T-bills, equity and commodity basis exposure, and prime lending. Perpetual futures, once the primary return engine, now account for just 11% of backing.

If executed well, these new sources would decorrelate Ethena's yield from crypto cycles and provide a higher baseline yield for sUSDe. However, each new category introduces counterparty and credit exposures the pure delta-neutral model never had. In this case, the Risk Committee's sizing and monitoring become the load-bearing element of the new architecture.

BUIDL by Blackrock

Borja Neira | Website | Dashboard

BUIDL holds $2.5B as chain distribution shifts from Ethereum to Solana and BNB Chain

BUIDL is BlackRock's tokenized money market fund, offering institutional investors exposure to short-term US Treasuries through an onchain wrapper. It recently lost its lead position by market cap to USYC. BUIDL’s market cap peaked at $2.92B in May 2025 before drawing down to $1.74B by year-end. As of April 2026, market cap has recovered to $2.47B, roughly flat YoY but up $730M (+42%) YTD.

The recovery was not driven by Ethereum, where supply contracted from $2.25B to $1.24B over the past year. Instead, growth came from new chain deployments. Solana ($527M, 21%) and BNB Chain ($508M, 21%) now account for 42% of outstanding supply, up from zero 12 months ago. What was once a single-chain product now spans eight networks. The flat YoY growth headline obscures a meaningful structural shift in chain distribution underneath.

Closing Thoughts

Yield-bearing tokens are scaling fast. USYC crossed $2.9B in under a year, BUIDL now spans eight chains, and sUSDe's staking ratio climbed to 60% even as USDe supply contracted. Capital is not just moving onchain. It is increasingly being allocated toward productive yield once it arrives.

But AUM only tells part of the story. The next phase hinges on whether these tokens integrate into onchain liquidity, credit, and collateral layers. The tokens that earn their place in DeFi will be the ones that become more capital efficient and composable across lending, borrowing, and settlement.

As these tokens scale, the frameworks used to evaluate them must also evolve. A Treasury bill wrapped in a token, held on a specific chain, and managed by a specific issuer carries risks that traditional asset labels do not capture. Blockchain infrastructure risk and issuer risk are real. Ignoring either leads to an incomplete picture of what these tokens actually represent.

What We're Watching

• sUSDe APY and staking ratio

• Ethena Reserve Proposal

• DeFiLlama’s Aave TVL Methodology

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Stablecoin Research Analyst at Tether

• Senior Data Scientist at Phantom

• Senior Data Scientist at Mysten Labs

By J.W.

The article is also available on X.

Nexus is building Non-USD Stablecoin Dashboard, powered by Token Terminal, tracking issuance and activity across non-USD denominated stablecoins. The dashboard is a work in progress, and we welcome feedback as we continue to refine it.

The Gap: Non-USD Stablecoins vs. FX Reality

The stablecoin market surpassed $319 billion in April 2026, yet less than 0.3% of that supply is denominated in currencies other than the U.S. dollar. In traditional foreign exchange markets, non-USD currency pairs account for approximately 11% of the roughly $9.6 trillion traded each day. This divergence reflects both market dynamics and an infrastructure gap that has yet to be addressed at scale. The question is whether onchain DEXs, centralized exchanges, or a hybrid architecture of both will emerge as the primary venue for non-USD stablecoin trading.

The momentum behind non-USD stablecoins is clear:

• Circle’s EURC became the first MiCA-licensed euro stablecoin in July 2024. Post-MiCA, EURC volumes increased 1,139% and Societe Generale’s EURCV volumes rose 343%. Building on that momentum, a consortium of 12 European banks, including ING, UniCredit, BNP Paribas, and BBVA, formed Qivalis to launch a MiCA-compliant euro stablecoin in H2 2026.

  

  

• Japan’s JPYC launched as the country’s first regulated yen-backed stablecoin in October 2025, registered under Japan’s Financial Services Agency. Japan’s megabanks (MUFG, SMBC, and Mizuho) launched pilots for stablecoins and tokenized deposits in payments and interbank settlement.

  

• South Korea saw KRW1 launch on Avalanche in September 2025 and KRWQ debut on Coinbase’s Base in October 2025. KakaoBank advanced its won-pegged stablecoin preparations ahead of pending legislation.

• Singapore’s XSGD processed over $3.8B in cumulative onchain volume, expanding into cross-border settlement across ASEAN through partnerships with Grab and Ripple.

The pattern is clear: this is a wave of sovereign stablecoin issuance. Each jurisdiction is effectively betting that its currency deserves a position in the onchain settlement layer. If that bet pays off at scale, one piece of infrastructure becomes essential: the exchange layer between these currencies. The way this layer is designed and governed will determine how deep non-USD liquidity can become, how efficiently flows are routed, and where custodial, credit, and regulatory risks ultimately concentrate.

The FX Architecture Problem

A holder of EURC looking to pay a counterparty in KRW1 faces a structural problem. Today, no direct EURC/KRW1 market offers meaningful liquidity. The practical path requires two legs: EURC to USDC, then USDC to KRW1. Each step incurs costs and routes through the dollar as a pivot currency. This mirrors the pre-digital FX market, where emerging market pairs settled through dollar intermediation and correspondent banks captured spreads at every conversion.

The question is whether onchain infrastructure can compress or eliminate that two-leg structure, and whether DEXs, CEXs, or a hybrid model is best positioned to do so.

The Case for a DEX

Decentralized exchanges enable stablecoin-to-stablecoin swaps without requiring custody, counterparty onboarding, or time zone constraints. Beyond access, composability adds another layer of structural advantage. A DEX-native FX layer can integrate directly with lending protocols, payroll applications, and treasury management tools without bilateral agreements or KYC gatekeeping.

Geographic reach extends that utility further. A DEX deployed on a low-cost L2 can serve a user in Lagos, Bogota, or Manila with identical access and pricing. No correspondent banking relationship required. For emerging markets, this is not a marginal improvement. It is access to a functioning FX market where the local banking system does not provide one.

That model already exists in early form. Mento’s Fixed-Price Market Maker (FPMM) prices swaps against oracle-fed real-world FX reference rates rather than pool dynamics, eliminating the impermanent loss problem that makes traditional AMMs uneconomical for stablecoin LPs. Mento has processed $31B in cumulative DEX volume across 15 currency pairs, according to Artemis.

Where the DEX model breaks down: liquidity. A EURC/KRW1 pool on Uniswap will have far less liquidity than a USDC/KRW1 pool, and far less than either has against the actual Korean won interbank market. Thin liquidity leads to high slippage, and high slippage is a structural tax on every trade. The FPMM oracle approach mitigates pricing instability, but it introduces oracle risk. If the price feed is manipulated or delayed, the pool misprices the swap.

The Case for a CEX / Institutional RFQ Model

Institutional Request for Quote (RFQ) platforms offer a fundamentally different approach to onchain FX. Rather than relying on permissionless liquidity pools, they route price discovery through established market makers and settle onchain, combining the efficiency of traditional FX infrastructure with the speed and finality of blockchain settlement.

The model is already live at institutional scale. Kinexys Digital Payments by JP Morgan enables 24/7 onchain FX settlement across USD, EUR, and GBP for clients including Siemens, Ant International, and B2C2. Circle's StableFX, built on its Arc Layer 1 chain currently in testnet, follows a similar RFQ structure: multiple liquidity providers compete for each trade off-chain, with settlement onchain via smart contract escrow.

Centralized exchanges bring a different but complementary advantage. As more sovereign stablecoins are issued under frameworks like MiCA and the GENIUS Act, Binance, Coinbase, and OKX are well positioned to serve as early liquidity venues for new non-USD pairs, given their existing regulatory relationships and user bases.

The core value of this model is not better pricing. Interbank FX markets are already highly efficient. What the RFQ model offers is faster settlement, reduced counterparty risk, and 24/7 availability. A treasury team managing multicurrency operations does not need tighter spreads. They need to move euros into won at 11pm on a Sunday without waiting for a bank to open.

Where the institutional model breaks down: access. The RFQ model requires bilateral relationships with licensed counterparties. It works for the banks and institutions with Kinexys access. It does nothing for the logistics company in Bangkok that wants to pay a supplier in Mexico City, at least not yet. For businesses and individuals outside institutional onboarding pipelines, that gap is not a minor friction. It is a structural exclusion.

DEX vs. CEX: A Framework

The DEX and CEX models are not competing for the same market. They solve different parts of the FX stack, with structurally distinct addressable markets:

• Liquidity depth: CEX dominates major currency pairs. DEX has developed liquidity for established crypto-native pairs but remains structurally thin for emerging market pairs.

• Settlement risk: DEX eliminates counterparty exposure. Smart contract escrow ensures both sides settle simultaneously or not at all. CEX achieves equivalent outcomes through RFQ but relies on contractual rather than programmatic guarantees.

• Access: DEX is permissionless by design, requiring only a wallet. CEX demands bilateral agreements, KYC onboarding, and licensing, gating institutional quality behind institutional friction.

• Composability: DEX can integrate natively with DeFi lending, payroll, and treasury protocols. CEX settlement requires additional steps to deploy in DeFi.

• Regulatory posture: CEX operates within familiar banking frameworks. DEX regulatory treatment remains unsettled in most jurisdictions. MiCA’s permissionless DeFi carve-out is provisional.

• Geography: DEX is globally accessible and most useful in markets with weak correspondent banking. CEX excels in corridors where both counterparties sit within regulated financial systems.

The most probable outcome is not binary. It is hybrid architecture. Institutional RFQ rails handle wholesale flows between regulated entities. Onchain AMM and FPMM liquidity serves retail, DeFi, and emerging market corridors. The layers are complementary, not competing. The question is which player captures which layer.

Closing Thoughts

Closing the gap between traditional FX markets and non-USD stablecoin pairs will not happen through a single model. In the near term, institutions will gravitate toward centralized venues for the liquidity depth and settlement guarantees they already understand. DEXs are better positioned to start narrow, building liquidity in a few high-volume cross-currency pairs and expanding from there as liquidity deepens and oracle infrastructure matures. The transition will be gradual.

Over time, the DEX model wins on access, composability, and reach, which matters most in emerging markets where correspondent banking is weak and routing through the dollar adds unnecessary friction. The CEX and RFQ model wins on liquidity depth, settlement guarantees, and institutional trust for large wholesale flows. Neither solves the full stack alone. The architecture that ultimately scales will be hybrid.

The most likely path forward mirrors what happened in perpetual DEX markets. Small protocols will launch as experiments, prove product-market fit in specific corridors, and gradually scale into infrastructure. The window to capture that layer is open. But it will not remain so indefinitely.

Sources & Data References

• BIS Triennial Central Bank Survey 2025

• Token Terminal — Non-USD stablecoin supply, April 2026

• Circle — MiCA licensing announcement, July 2024

• BBVA — European bank consortium announcement, Feb 2026

• Decta — Euro Stablecoin Trends Report 2025

• Tiger Research — 2026 Asia Stablecoin Market Overview

• The Block — KRW1 on Avalanche, September 2025

• The Block — KRWQ on Base, October 2025

• CoinDesk — Ripple partnership, May 2025

• GeckoTerminal — EURC/USDC pool on Uniswap V3

• Artemis — Mento Cumulative DEX volume, April 2026

• JP Morgan — Kinexys Digital Payments

• Arc Network / Circle — StableFX on Arc testnet, December 2025

Welcome to the seventh edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to Filippo, J.W., Owen, and Diego for contributing to this issue.

What We're Building

Over the past few weeks, Nexus has been working with Token Terminal to build a local stablecoins dashboard. That work became the spark for this issue. The further we went into the data, the clearer it became that non-USD stablecoins deserve dedicated analysis. The dashboard is still a work in progress, and we welcome feedback as we continue to refine it.

Setting the Scene

Stablecoins have found one of the clearest product-market fits in crypto. Total supply has crossed $294B, with USDT and USDC accounting for ~85% of the market. But that dominance obscures a structural gap.

In global FX markets, the US dollar is involved in 89% of transactions. Every one of those trades has a second currency on the other side. Onchain, that second half barely exists. Non-USD stablecoins represent just 0.33% of total stablecoin supply. The global economy is multi-currency, but onchain finance is not.

That gap is a product of how the market was built. Early stablecoins were designed for traders, and dollar-denominated liquidity became the default unit of account, collateral, and settlement layer across crypto. That works for a fraction of the world. For most of the world, transacting in USD stablecoins introduces constant FX exposure into everyday financial activity. Local stablecoins flip that equation. The rails stay global, but the unit of account becomes local.

This week, we cover the leading stablecoins across three non-USD currency segments: $EURC for euros, $ZCHF for the Swiss franc, and $BRZ for the Brazilian real.

Overview

Filippo | Website | Dataset

Non-USD stablecoin supply crosses $2.3B, but growth and adoption tell different stories

According to Dune, non-USD stablecoin supply has crossed $2.3B, expanding 2.3x in 12 months. But the distribution behind that number is uneven, and the headline figure obscures a fragmented picture beneath it.

A7A5, a ruble-pegged stablecoin, accounts for the largest share of that growth, expanding 8.4x to $1.17B across 36K wallets. EURC reached $476M, up 1.8x, with 203K holders and the widest retail distribution among large non-USD stablecoins. JPYC went from a single holder to 45K in under a year, the fastest onboarding ramp in the category. EURA still reports roughly 797K holders against only $4M in supply, and with Angle Protocol announcing its discontinuation in March 2026, that holder base is winding down.

Euro-pegged stablecoins remain the most diverse category by both supply and holder count. But across the broader non-USD landscape, supply growth and holder growth are moving at different speeds and in different directions.

Euro Stablecoins ($EURC)

Owen Fernau | Website | Dashboard

EURC holder count grows 2.2x faster than supply

EURC, a euro-pegged stablecoin issued by Circle, is the largest non-USD stablecoin by market cap at $476M, representing just over half of all non-USD stablecoin supply combined. This excludes A7A5, a ruble-pegged stablecoin that, due to international sanctions on Russia, is not tracked by most data providers.

Since January 2025, supply has grown 286% while holder count climbed 633%, with holders growing 2.2x faster than supply. One interpretation is that EURC is becoming diluted as new holders enter. Each holder represents a proportionally smaller share of total supply than 16 months ago, even as overall supply has expanded. That pattern is consistent with organic adoption rather than concentration.

EURC's growth story points toward broader distribution. The question now is whether Circle can convert that expanding base into an actively transacting network, or whether EURC settles into a compliance-driven store of value rather than a functioning payments rail.

Frankencoin ($ZCHF)

J.W. | Website | Dashboard

ZCHF market cap reaches $38M with 89% growth in 2026

Frankencoin (ZCHF) is the largest CHF stablecoin onchain, pegged 1:1 to the Swiss franc. Unlike USDT or USDC, no company holds reserves in a bank account to back it. ZCHF is minted by users who lock up crypto as collateral directly onchain, and if that collateral loses value, it is liquidated automatically to protect the peg.

The mechanism is deliberately different from most collateralized stablecoins. Rather than relying on external price feeds to trigger liquidations, ZCHF uses an auction process. When a position is challenged, the market bids on the collateral over a period of days rather than minutes. The architecture makes it slower, but removes a vulnerability that has cost DeFi protocols hundreds of millions in oracle manipulation attacks. A set of economic constraints pushes the market toward parity from two sides, incentivizing arbitrage whenever ZCHF deviates.

The protocol runs on two tokens. ZCHF is the stablecoin. Frankencoin Pool Shares (FPS) represent ownership in the protocol. FPS holders earn protocol fees and liquidation proceeds, but they are also the first to absorb losses if the system becomes undercollateralized.

ZCHF's market cap reached $38M while average wallet balance declined from roughly $90K to under $25K. Early data suggests organic adoption may be broadening beyond the protocol's early users, though it is too soon to draw firm conclusions. Average balance alone captures only one dimension of that distribution. Growing market cap paired with an expanding holder base will determine whether ZCHF's trajectory reflects structural demand or remains a niche footnote in the stablecoin market. Until that scale is reached, ZCHF remains a proof of concept rather than a functioning alternative to dollar-based stablecoins.

Brazilian Digital ($BRZ)

Diego Cabral | Website | Dashboard

BRZ has processed $980M in volume in 2026 on $44.8M circulating supply

Transfero’s BRZ is the largest BRL-pegged stablecoin onchain, with $44.8M in circulating supply and $980M in transfer volume year to date. That is roughly a 20x supply turnover, a ratio more consistent with an active payment rail than a parked store of value.

Since early December 2025, circulating supply expanded rapidly from $19.7M to $44.8M, a 127% increase in under four months. Weekly transfer volume has held in the $30M to $70M range throughout.

On average, BRZ transfer volume drops 84% on weekends compared to weekdays. The average weekday sits around $14.7M while weekends come in at $3.4M. That pattern is a direct signal of payment orientation, consistent with payroll and B2B settlement cycles rather than speculative trading. Usage is leading supply growth, not the other way around. That is what a local-currency stablecoin functioning as a real payment tool looks like.

Editor's Note

The following two transactions are excluded from this analysis. The mint and burn activity appears to artificially inflate transfer volume:

• 0xca380e327a8c45c47624f55f8bf1d12c1c1c596ec84199e080d04e910e10b8e0

• 0x07697bc316c89a8134e98eddf1076a88260e8c02d77e70cbdbdca14f707109e4

Closing Thoughts

The US dollar is the world's reserve currency, and dollar-denominated liquidity was the natural starting point for a market built on global, permissionless rails. Dollar stablecoins won because they arrived first and solved the right problem for the right users at the right time. That progression made sense.

Local stablecoins represent the next phase. Not as competitors to USDT or USDC, but as missing infrastructure. As adoption moves from trading to payments, payroll, and treasury flows, the demand for onchain money that matches real-world liabilities becomes unavoidable. A business paying suppliers in euros, a freelancer receiving income in Japanese yen, a Swiss firm settling invoices in francs. None of them are naturally dollar users. Onchain rails that ignore that reality will remain incomplete.

What EURC, ZCHF, and BRZ each show, at different stages of maturity, is that local demand exists and is measurable onchain. The growth is uneven and liquidity remains thin relative to USD pairs, but the foundation is being laid. The next stage of stablecoin growth will not be won by one currency. It will be built currency by currency.

What We’re Watching

• Swiss banks to test CHF stablecoin

• DeFi Llama partners with Spark to launch an investor relations portal

• x402 vs MPP

• Dune x Visa report: “Beyond Dollarization”

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Data Scientist at Jito Foundation

• Data Analytics Engineer at Alchemy

• Data Analyst at Xapo

By J.W.

The article is also available on X

Setting the Scene

Polygon has evolved through several distinct strategic phases since its launch. What began as a scaling solution for Ethereum evolved into a gaming and NFT hub, then a DeFi settlement layer, and most recently a stablecoin and payment network. Across each phase, the underlying message has remained consistent: Polygon is built for broad, real-world adoption at scale.

The data, however, tells a different story.

In March 2026, a single application dominated Polygon’s network activity across various measurable dimensions, including transactions and gas fees, according to the Dune Dashboard. That application isn’t a stablecoin issuer or a payment provider. It’s Polymarket. By any infrastructure measure, Polygon’s blockspace economy is not a diverse ecosystem. It is, functionally, a prediction market chain with residual activity surrounding it.

The chain’s stablecoin data reinforces that point. According to RWA.xyz, Polygon hosts approximately $3.6B in stablecoins, a figure central to its payment settlement narrative. However, roughly $1.26B, nearly one in every three dollars, sits inside Polymarket alone: $413M in open interest across markets and $845M in user proxy wallets, according to @datadashboards on Dune. At a time when stablecoin infrastructure is one of the most closely watched growth vectors in crypto, a substantial portion of Polygon’s stablecoin supply belongs to a prediction market, not a payment protocol.

The Bear Case: Polygon's Single-App Problem

Polygon markets itself as "the go-to blockchain for global payments," positioning its chain as infrastructure for payments and stablecoins. In traditional financial infrastructure, settlement layers derive their resilience from diversity of demand. The more independent sources of fee revenue a settlement layer has, the more resilient its economic foundation becomes. This is not a crypto-native concept. It is the same logic that underpins payment rails and correspondent banking networks.

By that standard, the data presents a challenge for Polygon’s current positioning. A network where one application accounts for the majority of gas fees and compute load does not reflect the profile of a settlement layer. As of March 2026, Polymarket’s share of Polygon’s network activity tells that story plainly:

• Gas fees: 67.3%

• Compute units: 77.0%

• Transactions: 54.4%

It reflects a network where one protocol drives the majority of demand and everything else is residual. That concentration creates a structural dependency. Polygon’s fee revenue, throughput economics, and network utilization are substantially driven by a single protocol’s activity. At this scale, that concentration could pose a systemic risk to the network itself.

The Dependency Risk: What Happens If Polymarket Leaves?

This is not a hypothetical. Application-specific chains have become a trend with dYdX and Uniswap launching their own execution environments rather than remaining deployed as apps on shared networks. Polymarket has equal incentive to pursue its own chain as well. As the platform scales, the case for Polymarket controlling its own execution environment strengthens. A Polymarket L2 would preserve settlement flexibility while capturing fee revenue that currently accrues to Polygon validators.

If Polymarket migrates, Polygon does not gradually lose activity. It loses it overnight. Fee revenue collapses. Transaction volume craters. There is no second application waiting to absorb the load, at least not yet. What remains is a chain that once hosted the world's largest prediction market, now competing for relevance with a significantly thinner demand base, unless another Polymarket comes along.

The Bull Case: Polygon’s Memecoin Moment

Despite the bear case built around Polymarket’s concentration, there is a credible counterargument. Polygon’s relationship with Polymarket mirrors Solana’s rise in 2024. As memecoin trading volumes exploded, a single sector dominated blockspace demand and fee generation, ultimately driving $SOL’s price appreciation alongside it. So far, however, $POL has not reflected that dynamic in its price performance, despite the structural parallels.

There may be another catalyst on the horizon. In October 2025, Polymarket CMO Matthew Modabber confirmed that a $POLY token and airdrop are coming, stating “There will be a token, there will be an airdrop.” For Polygon, that confirmation carries implications that extend beyond Polymarket’s own token economy. When $POLY launches, the airdrop creates an entirely new class of economically motivated participants. Recipients will claim tokens, trade them, speculate on price, and rotate into and out of Polymarket to farm further rewards or express views on $POLY itself. Each of those actions generates a transaction that settles on Polygon. A $POLY launch does not just benefit Polymarket in isolation. It would hand Polygon a demand spike, layering a second catalyst on top of a network already running at concentrated capacity. Fee revenue climbs, compute utilization rises, and the network metrics that currently reflect one dominant application compound further, assuming Polymarket stays.

Closing Thoughts

Whether Polymarket ultimately migrates or Polygon captures the $POLY airdrop tailwind remains an open question. Polygon’s relationship with Polymarket is symbiotic, for now. Polymarket gets reliable, low-cost settlement infrastructure. Polygon gets sustained, organic blockspace demand. The arrangement has worked.

In the near term, the arrangement will likely hold. Polymarket’s immediate priority is market share, not chain migration. The fight with Kalshi is accelerating, and building a new execution environment requires resources, engineering time, and operational risk that no platform mid-battle can easily justify. As long as the current infrastructure holds, there is no obvious trigger to move.

But that stability may not last forever. One application controls 77% of Polygon’s compute and holds nearly one in every three dollars of its stablecoin supply. That is a single-app concentration risk embedded in Polygon’s market position, and one the data surfaces whether the narrative acknowledges it or not.

Welcome to the sixth edition of Nexus Data Labs, where we highlight what matters most in the fast-developing world of onchain finance.

Thank you to J.W., Owen, and Diego for contributing to this issue.

Setting the Scene

The last edition opened the door on AI x blockchain infrastructure. This week we go deeper on two of the most active developments in that space: x402, an emerging payment framework enabling AI agents to transact autonomously onchain; and Bittensor, a decentralized network turning artificial intelligence into an open market. One is building the payment rails while the other is building the marketplace where AI models compete to produce intelligence. Both are early and moving fast.

x402

Owen Fernau & J.W. | Website | Dashboard

Approximately 38% of x402 cumulative transactions appear inorganic

x402 is a payment protocol built for the internet’s next layer: machine-to-machine transactions. The name comes from HTTP status code 402, “Payment Required”, a code that has existed in web standards since 1991 but was never formally implemented. x402 activates it. The core idea is simple. Rather than a human logging in, entering card details, or approving a transaction, x402 allows AI agents and software programs to pay for data, APIs, and services autonomously. For developers building AI agents that need to consume external data or services, x402 offers a standardized way to handle payments onchain without custom billing integrations.

Since launching in May 2025, x402 has processed over 166M cumulative transactions across $47M in total volume. But not all of that activity reflects genuine economic demand.

Artemis identifies two forms of artificial activity on x402: self-dealing, where the same wallet acts as both buyer and seller; and wash trading, where a seller wallet funds a buyer wallet that immediately returns the funds. Together, these two patterns account for approximately 38% of cumulative transactions.

The infrastructure is being built. Developers are integrating x402 into agent frameworks, standardizing payment flows, and shipping tooling. What has not yet materialized is sustained organic usage at scale. The protocol has a foundation. The next phase depends on whether genuine commercial demand grows into it.

Bittensor ($TAO)

J.W. | Website | Dashboard

$TAO rallied 88% in March 2026 as Covenant-72B validated decentralized AI training at scale

Bittensor is a decentralized network designed to transform artificial intelligence into an open market. Rather than concentrating AI development within a handful of large organizations, it enables anyone to build, contribute, and earn from machine intelligence at a global scale.

The network is organized around subnets, each an independent AI marketplace dedicated to a specific task. A subnet can focus on anything from large-scale model training and decentralized inference to GPU compute and financial prediction. Within each subnet, two classes of participants interact:

• Miners supply the intelligence. They run models, process data, and produce outputs.

• Validators measure quality. They assess each miner's contribution and determine who performed best.

Every day, a fixed pool of $TAO is distributed across the network. Subnets compete for their share by producing verifiable AI work. Those delivering the strongest results attract the most participants and capture the largest share of daily emissions.

In March 2026, $TAO moved from $177 to $333, an 88% gain that outpaced a broader market deep in the red. Subnet market cap climbed to $1.38B over the same period, with individual tokens ranging from $1M to $126M and several subnet tokens posting 200–400% monthly gains.

Two catalysts drove the move:

• Covenant-72B: Subnet 3 (Templar) completed the largest decentralized AI model training run across more than 70 contributors worldwide using ordinary consumer hardware. The model performed on par with one of Meta's most capable open-source models, Llama 2 70B. Before Covenant-72B, decentralized AI training at this scale was theoretical, but the model made it real.

• Jensen Huang: On Mar 20, 2026, Nvidia CEO Jensen Huang endorsed Bittensor’s decentralized training model on the All-In Podcast, framing it as complementary to proprietary AI development. Coming from one of the most influential voices in AI infrastructure, the endorsement carried weight far beyond the usual crypto audience.

AI narratives are moving fast, and $TAO is riding that wave. The real test is whether subnets can sustain organic demand. Bittensor is among the most serious decentralized AI infrastructure experiments running today. Whether that translates into durable product market fit remains an open question, but the network is no longer just making promises.

Closing Thoughts

Bittensor and x402 represent two distinct but converging bets on where AI infrastructure is heading. Bittensor treats intelligence itself as a commodity, routing capital toward the subnets producing the most verifiable AI work. x402 removes the human from the payment loop entirely, letting agents pay for data and services autonomously. Together they sketch an early picture of what AI-native infrastructure looks like in practice.

Both protocols remain in a phase where narrative still runs ahead of usage data. Bittensor's subnet economy runs on daily emissions. x402's transaction base is roughly 38% inorganic. The infrastructure is being built and the direction is clear. What's still missing is real, sustained demand.

The protocols that close that gap will define which parts of the AI x blockchain stack actually matter. Everything else is infrastructure waiting for a use case.

What We’re Watching

• The Bear Case for Bittensor (TAO)

• Covenant-72B on Templar

• x402’s Wash Trading Problem

• Introducing x402 Foundation

Web3 Data Jobs

Nexus is partnering with Unchain Data to highlight opportunities across the onchain data ecosystem. This week’s featured openings:

• Data Analyst at Kraken

• Head of Data at Solana Foundation

• Senior Data Scientist at Coinbase

Welcome to the fifth edition of Nexus Data Labs. Our aim is to highlight what matters most in the fast-developing world of onchain finance.

Thank you to J.W. and Diego for contributing to this issue.

Setting the Scene

The intersection of AI and blockchain is rapidly evolving from concept to infrastructure. Over the past year, autonomous agents, payment rails, and specialized data layers have begun operating directly within onchain systems, not as experiments, but as functional components of an emerging tech stack.

This shift raises an important question for the onchain economy: what happens when AI agents, rather than humans, become its primary users? For onchain analysts, the question is more immediate: how is AI changing the research toolkit?

This week's edition explores how the transition is beginning to take shape, through a key development at the frontier: a new generation of Large Language Models (LLMs), Model Context Protocols (MCPs), and Command Line Interfaces (CLIs) tools allowing AI systems to interface directly with structured data providers.

Across all the offerings, a common thread is emerging: the tools used to analyze the onchain economy are evolving alongside the economy itself.

The Agent Interface Layer

Diego Cabral

How data providers are opening their datasets to AI agents, through LLMs, MCPs and CLIs

Over the past few weeks, a growing number of data providers have started experimenting with interfaces designed specifically for AI agents. By exposing their datasets and analytics tools through LLMs, MCPs, and CLIs, these teams are shifting agents’ role from passive assistants to active research operators, capable of querying, analyzing, and synthesizing information directly from the source.

In the section below, a few of the teams at the frontier of onchain data share how they see analysis evolving in the age of AI agents.

Note: The tools featured here were chosen for relevance, not commercial relationships.

Allium

AI agents in crypto can already transact and make decisions without human intervention. What they cannot do reliably is verify the state of the blockchain they are operating on.

Two recent standards address parts of this problem. ERC-8004 gives agents a way to identify and establish trust with each other. The x402 payment protocol lets them transact autonomously per request. Taken together, they remove two significant constraints on autonomous agent activity in crypto.

But neither standard solves the data layer. Agents need to read protocol state, validate outcomes, and act on what is actually happening onchain. Raw blockchain data does not support this. It is fragmented across chains, encoded in low-level formats, and inconsistent without significant preprocessing. An agent operating on that layer does not fail immediately. It keeps executing on incorrect data, at machine speed, until enough errors accumulate to surface.

The bottleneck for agentic economies is not model capability or transaction infrastructure. It is whether agents have access to structured, accurate onchain data. Without it, AI applications, MCPs, and agent skills cannot operate reliably regardless of how sophisticated the models above them are.

Without writing a single line of code, the Allium MCP and Claude Cowork enabled us to produce a working x402 data dashboard.

More on Allium

Dune

Historically, extracting value from onchain data required SQL fluency, Dune’s schema knowledge, and an account. Dune’s recent AI developments and features remove that barrier.

Over the past two weeks, Dune shipped the access layer.

The Dune MCP Server gives GUI-based AI apps like Claude, ChatGPT, and Gemini structured access to the full Dune workflow: discover tables, write DuneSQL, execute queries, and generate visualizations in a single conversation.

The Dune CLI & Skills extends that same access to terminal-native agents such as Claude Code, Cursor, OpenCode, via a Go-based CLI and a bundled Skills.md file that lets any agent understand Dune’s full toolset with no custom integration required.

MPP (Machine-Protocol-Payments built by Stripe & Tempo) completes the stack. Agents can now discover tables, write DuneSQL, execute queries, and pay for results with no account, no API key, and no human in the loop.

The pattern is simple: agents should query data the way analysts think about it. Dune is building the infrastructure layer to make that real.

We used Dune’s MCP and Claude to build a prediction markets dashboard that pulls data directly from community queries on the platform with no coding involved.

More on Dune

Surf

Although crypto is one of the most data-rich industries, analysis across sources remains a challenge even with AI.

In most industries, data is accessible enough that AI can work with it effectively. In crypto, data is fragmented, and connecting the dots requires context that cuts across sources.

The industry’s attempt to solve this led to over-applying AI vertically. AI was layered onto existing data products, making individual platforms easier to use. Understanding one source at a time became simpler, but synthesis did not.

Comprehensive analysis requires orchestrating multiple data sources, agents, and models around a single objective. Optimizing for one piece of the puzzle adds to the fragmentation rather than resolving it.

As this trend of verticalization accelerates, so will demand for products that take a different approach. Surf is building AI designed for crypto and capable of reasoning across all of its data.

Using Surf Studio, a chatbot-style interface, we built a Hyperliquid dashboard highlighting HIP-3 and HIP-4 testnet data with only language prompts.

More on Surf

Token Terminal

AI assistants make it possible to query onchain data by chatting, removing the need for manual workflows such as navigating dashboards, exporting data, or writing queries.

However, this introduces a constraint: human queries are ambiguous, while data systems require precise definitions. Without a mechanism to translate intent into machine-readable instructions, the model cannot reliably map questions to data, resulting in inconsistent outputs.

This limitation is compounded by context constraints in the underlying language models, which cannot reason over a complex data system’s full structure in a single pass.

Token Terminal MCP addresses this through an intermediate reasoning layer. User queries are first processed by an offline discovery system that maps intent to a structured taxonomy spanning market sectors, projects, metrics, and methodologies. This resolves ambiguity before any query is executed.

The result is a deterministic interface between natural language and structured data. The model operates within the constraints of a system of record, enabling reliable access to standardized onchain data.

We explored Token Terminal’s MCP and produced a comprehensive non-USD stablecoins dashboard. Although the project is still experimental, it is already one of the most extensive dashboards tracking local stablecoins available today.

More on Token Terminal

Closing Thoughts

The infrastructure connecting AI agents to onchain systems is still early, but the direction is clear. Payment rails, data access layers, and agent-native protocols are moving from whitepaper concepts to functional deployments.

Unlike traditional tools built around human workflows, this new layer is optimized for machine consumption. Data providers across the ecosystem are actively experimenting with these integrations.

At the same time, the role of human analysts remains central. AI can accelerate research workflows, assist with data exploration, and automate parts of the analytical process. But effective research still depends on asking the right questions and interpreting results within the right context.

The opportunity ahead is not replacing analysts, but expanding what they can do. As these tools mature, the bottleneck shifts from data access to problem framing. Researchers who use that leverage well will move faster, cover more ground, and extract clearer signal from the onchain economy.

What We're Watching

• Open Agentic Commerce

• MPP vs. x402

• Is Crypto Even Necessary for Agentic Commerce?

• DeFi Llama introduced its MCP

Welcome to the fourth edition of Nexus Data Labs. Our aim is to highlight what matters most in the fast-developing world of onchain finance.

Thank you to Filippo, Peter, J.W., and Diego for contributing to this issue.

Setting the Scene

Prediction markets entered the spotlight during the 2024 U.S. Presidential election. What had been considered a niche corner of the onchain economy became part of the mainstream conversation overnight. The question that followed was simple: would prediction markets survive once the election hype faded?

The 2025 data delivered a resounding answer: yes. Starting in September 2025, the sector began posting volumes that matched and then exceeded previous cycle highs. October 2025 marked a new all-time high for notional volume, followed by consecutive monthly records through January 2026. That growth has since drawn a new wave of prediction markets into the space.

It is worth noting that while Polymarket and Kalshi currently dominate the space by volume, Nexus focuses exclusively on blockchain-based activity. Coverage is scoped to Kalshi's onchain activity and its partnership with DFlow, which provides tokenization infra for prediction markets.

Overview

Filippo | Dashboard

Prediction markets grew 225x in two years — Sports now lead

The prediction market sector grew 225x in two years, from $103M to $23.2B in monthly volume.

Polymarket rebounded after the 2024 election to reach $7.9B in monthly volume in February 2026 —nearly twice its prior peak— but lost share as rivals scaled faster. Kalshi climbed from $1.2B to $10.4B in monthly volume, rising from under 3% share to 45%, while Opinion reached 30% share within months.

Across Polymarket and Kalshi, sports led category share at 64.4%, followed by crypto at 18.1% and politics at 10.6% as of February 2026. This is largely driven by Kalshi's aggressive expansion into sports event contracts. Polymarket's mix is more balanced across crypto, politics, and entertainment.

Polymarket

Peter | Website | Dashboard

Polymarket posts $7.94B in February 2026 volume as bet activity surges 55% month-over-month

Polymarket continues to see accelerating growth across trading activity and trader capital. The platform has generated over $61B in cumulative trading volume. In February 2026, $7.94B was traded, up 3.7% from January's $7.66B. Participation is also rising, with 80.7M bets placed in February, up 55% from 52M in January.

Trader capital has expanded alongside activity. As of February 2026, approximately $336M is held across Polymarket proxy wallets, up from $37M in October 2024, representing over 9x growth in 16 months.

Taken together, rising volumes, bet activity, and trader capital highlight the maturation of onchain prediction markets.

Polymarket vs. Polygon

J.W. | Website | Dashboard

Polymarket is Polygon's biggest tenant, consuming 77% of its blockspace

Polymarket isn't just the dominant prediction market. It is now the dominant application on Polygon itself. In March 2026, the platform consumed 77% of all compute units on the network, generated 67.6% of gas fees, and accounted for 54.4% of total transactions. By any infrastructure measure, one application has effectively become the chain's anchor tenant.

While network usage exceeds 50% of Polygon, Polymarket traders represent only 19.7% of daily active users on Polygon. That asymmetry raises a question worth examining: is this healthy concentration or structural dependency? The bull case is straightforward: Polymarket is a world-class application generating sustained, organic demand for Polygon blockspace. The bear case is equally clear. A single application generating the majority of network gas means Polygon's throughput economics are effectively tied to one protocol's growth trajectory. If Polymarket migrates, scales to its own chain, or slows down, the network metrics will follow.

For now, the numbers reflect a symbiotic relationship that has worked. Polygon provides the settlement layer; Polymarket provides the demand. Whether that concentration becomes a liability depends on what Polygon builds next.

Kalshi Onchain Activity

Diego Cabral | Website

Kalshi's onchain weekly volume peaks at $10M - Under 0.3% of total activity

While Kalshi has been experimenting with integrations across major Solana distribution channels, including DFlow, Phantom, and Jupiter, to make its markets accessible onchain, the strategy has yet to generate meaningful volume.

At its highest point, onchain notional weekly volume reached roughly $10M. To put that in context, Kalshi processed $1.9B in total notional volume during the week of Jan. 1 2026, making the onchain $10M peak just 0.53% of total activity. By the week of Feb. 1 2026, total weekly volume had risen to $2.19B, pushing that same $10M peak down to 0.46%. Onchain flow remains well under 1% of Kalshi's total trading volume, suggesting that the current distribution strategy has yet to materially expand market access or user interest.

Closing Thoughts

Prediction markets have proven they can grow beyond election cycles. Sports and politics have always been the two headline themes, and 2026 brings one of the largest global sporting events, the FIFA World Cup, which is likely to drive a fresh wave of users to the sector.

High-profile events have historically served as a natural entry point for new participants, many of whom go on to explore other categories. Whether those users remain active beyond event-driven speculation, however, remains the sector's defining open question.

On the regulatory front, clarity may also play an increasingly important role. Early steps toward clearer frameworks, such as the recent CFTC proposal, could reduce uncertainty and broaden institutional participation, creating a more stable foundation for long-term adoption.

What We're Watching

• 564 Unusual Wallets Betting $2.9M on the Iran War

• The Call for Standardizing Stablecoin Volume Metrics

Next Week

Next week, we turn to the intersection between AI and the onchain economy, covering x402, the TAO ecosystem and how different data provider are approaching the use of AI for data analysis.

Intro

Welcome to the third edition of Nexus Data Labs. Our aim is to alert you to what really matters in the fast-developing world of onchain finance.

Thank you to Diego, and Owen, and J.W. for contributing to this issue.

Setting the Scene

Over the past two years, perpetual DEXs have evolved from a DeFi experiment into one of the most competitive frontiers in onchain trading — pulling derivatives trading that once belonged almost exclusively to centralized exchanges into a trustless, self-custodial environment.

As scaling solutions mature and liquidity deepens across L2s and high-performance chains, the performance gap between onchain venues and centralized exchanges, once thought to be out of reach, has narrowed dramatically.

Perpetual futures, derivatives with no expiry date that allow traders to go long or short with leverage, require no custody of the underlying asset and no rolling of contracts. What began as an attempt to replicate centralized markets onchain has since evolved into a diverse and highly competitive ecosystem.

This week’s edition highlights four platforms leading that next phase of perp DEXs: Hyperliquid’s HIP-3 Deployers, Lighter, Aster, and GRVT.

Perp DEXs Overview

Diego Cabral | Dashboard

Perp DEX sector daily volume is up 35% from 2025, annualizing to $11.17T

Growth in the perp DEX sector is accelerating: daily average trading volume jumped from $7.5B (2024) to $22.7B (2025) and $30.6B (2026 YTD). That is a 35% increase from the previous year's average, which was approximately 3x higher than the year before.

With $2.08T volume in just 69 days this year, the sector is on pace for $11.17T annually, representing a 34% increase from 2025's full-year total. Hyperliquid maintains sector dominance at 22.4% of volume, while Aster and Lighter account for roughly 31% combined.

The numbers suggest 2025 was the adoption phase; 2026 is the growth phase, an era of higher capital efficiency, and intensifying institutional participation driving volume to record levels.

HIP-3 Perp DEX

J.W. | Website | Dashboard

HIP-3 tops $98B in cumulative volume amid weak market sentiment

Hyperliquid Improvement Proposal 3 (HIP-3) is a significant protocol upgrade enabling permissionless, decentralized creation of perpetual markets. Any user can now deploy a perp market by staking 1M $HYPE. This removes gatekeepers from market creation entirely.

Since deployment, cumulative trading volume has surpassed $98B. TradeXYZ, a perp market deployer, has emerged as the dominant venue, capturing 83.9% of volume and 87.6% of open interest. Dreamcash and Felix round out the early competitive set. As of March 2026, total daily open interest holds above $1.2B — a signal that the upgrade is generating sustained activity, not just initial noise.

Perhaps the more consequential story is what HIP-3 enables beyond crypto-native assets. Builders are already deploying markets for TradFi instruments — Nvidia, Anthropic, and uranium among them — effectively using Hyperliquid as infrastructure to bring traditional asset classes onchain. If that trend continues, HIP-3 could represent something larger than a protocol upgrade: a meaningful step toward converging onchain and TradFi markets.

Lighter

J.W. | Website | Dashboard

Lighter’s TVL plummet by 54% post airdrop

Lighter is a perpetuals DEX built as a ZK-rollup on Ethereum. At its peak, daily perp volume surpassed $18.9B with TVL exceeding $1.4B. These metrics spiked sharply in Q4 2025 as anticipation around an airdrop built.

On Dec. 30, 2025, that speculation was confirmed: Lighter distributed 25% of its native token, $LIT, in one of the more closely watched token launches of the year. However, post-airdrop data has since answered the underlying question. As of March 2026, TVL has fallen to ~$600M and daily perp volume has retreated to the low single-digit billions, marking a significant drawdown from peak levels.

Aster

Owen Fernau | Website | Dashboard

Aster perp volume and token price both down over 60% from late 2025 highs

Aster is a perp DEX that consistently ranks in the top 5 by volume according to DefiLlama. As of March 2026, Aster ranks second among perp DEXs with $78.6B in volume over the past 30 days.

The $ASTER token is down 67% to $0.69 from its $2.07 October 2025 peak. At $18.1B, perp volume is down 76% from its mid-October weekly peak of $76.6B. Volume exploded when the $ASTER airdrop hit in late September 2025. It remains to be seen whether the token can sustain itself as incentives taper off.

Only 35.1% of $ASTER tokens are unlocked as of March 2026, meaning the market will eventually need to absorb the remaining 63.9% of the token supply to even maintain its price level of $0.70.

GRVT

Diego Cabral | Website | Dashboard

GRVT grows 340% year-over-year: weekly volume surges from $2.2B in 2025 to $9.7B in 2026

GRVT is experiencing fast growth in a competitive sector, with 2026 YTD weekly volume averaging $9.7B, a 377% increase from 2025's $2.19B weekly average. The protocol has accumulated $104B in 2026 YTD, annualizing to a $540B run rate versus $113.70B for full-year 2025 — signaling a potential 4.8x expansion trajectory.

While still trading at 21% of Hyperliquid’s 2026 volume, GRVT has captured significant market share. Its $470M open interest reflects a growing user base. Weekly volumes peaked in late January 2026 at $14.47B before moderating to $10.27B in early March 2026, consistent with sector activity but at dramatically higher absolute levels than the previous year. GRVT's momentum suggests emerging product-market fit and/or user migration after Lighter’s airdrop.

Closing Thoughts

This week’s insights highlight that perpetual DEXs are clearly past the “experiment” phase. Sector-wide volumes are compounding, new architectures like HIP-3 are onboarding non-crypto assets, and challengers such as Lighter, Aster, and GRVT have shown they can briefly rival incumbents.

However, the data also makes one point clear: initial spikes driven by incentives and airdrops are not enough. What ultimately matters is how much volume, open interest, and liquidity remain once the rewards fade.

The protocols that maintain depth and activity after incentives fade — through better execution, differentiated markets, and credible paths to real economic use — are the ones most likely to shape the next generation of onchain derivatives infrastructure.

What We're Watching

• The Stablecoin Data Gap

• Status of HIP-3 Market

Next Week

Next week, we turn to prediction markets, to analyze the growth and usage of one of the hottest sectors of the onchain economy.

Intro

Welcome to the second edition of Nexus Data Labs. We’re here to tell stories about onchain data. Our aim is to alert you to what really matters in the fast-developing world of onchain finance.

Thank you to Borja Neira, Frederick Hopkins, Diego Cabral, and Meta for contributing to this issue.

Setting the Scene

Real-World Assets (RWAs) continue to transform from a niche crypto experiment to a key area of focus for traditional finance.

With institutions deepening their RWA offerings — from asset managers tokenizing treasuries to investment banks exploring private credit rails — tokenized assets have become a barometer for traditional finance’s adoption of blockchains.

The direction is clear: the question is no longer if assets will move onchain, but which assets, when, and, subtly, what the underlying ownership and legal architecture actually looks like.

This week’s edition highlights three dimensions of the RWA landscape making headlines: the growing adoption of Tokenized Gold, the expanding market for Tokenized Stocks and US Treasuries, and the challenging integration of RWAs within DeFi protocols.

RWA Overview

Borja Neira | Website | Dashboard

Tokenized assets hit $24.9B, up 289% year-over-year, as six sectors cross $1B

Tokenized assets (excluding stablecoins) reached $24.9B as of Feb. 19, 2026 — nearly 4x from $6.4B a year prior (+$18.5B, +289%). U.S. Treasuries and commodities drove 58% of year-over-year growth, adding $6.8B and $4.0B respectively.

The defining shift was breadth: asset classes exceeding $1B grew from two to six, with private credit ($2.9B), institutional funds ($2.0B), corporate bonds ($1.7B), and non-U.S. government debt ($1.0B) all crossing the threshold — collectively contributing 37% of total growth. Treasury market share declined from 59% to 43%, signaling a more diversified market.

Tokenized US Treasuries

Borja Neira | Website | Dashboard

Tokenized U.S. Treasuries reach $10.8B, up 183% year-over-year, as offerings grow from 35 to 53 and top-3 concentration falls from 61% to 48%

Tokenized U.S. Treasuries nearly tripled to $10.8B from $3.8B a year ago (+$7.0B, +183%), with active products growing from 35 to 53 as new funds from Fidelity, ChinaAMC, and VanEck entered the market.

BlackRock's BUIDL rose from $0.6B to $2.2B (+239%), overtaking Hashnote's USYC to become the largest tokenized Treasury product at 20% market share. Ondo's combined exposure — OUSG ($0.7B) and USDY ($1.3B) — reached $2.0B, while newer entrants scaled rapidly: Superstate's USTB ($0.8B, +499%), WisdomTree's WTGXX ($0.7B, +759%), and ChinaAMC ($0.6B, from $0). Together, these dynamics pushed top-3 concentration down from 61% to 48%, reflecting a more fragmented and competitive market.

Tokenized Stocks

Frederick Hopkins | Website | Dashboard

Tokenized stocks grew from near-zero to $786M since mid-2025, making them the newest yet fastest-growing category of tokenized assets

Since mid-2025, tokenized stocks have scaled from near-zero to $786M — driven by a expanding roster of issuers including Ondo Finance, Backed Finance, Spiko, Robinhood, Dinari, Remora Markets, and Superstate. These platforms tokenize both individual equities — NVDA, GOOGL, and TSLA — and ETFs like SPY and QQQ, which track the S&P 500 and Nasdaq-100, enabling 24/7 trading with near-instant settlement.

Market cap growth accelerated even as Bitcoin dropped below $70K — a sign that onchain demand for equity exposure may be developing independently of broader crypto market sentiment.

Tokenized Gold

Diego Cabral | Dashboard

Tokenized gold circulating supply nearly doubled from 687K to 1.3M troy oz over the past 12 months, as gold spot price surged 80% from $2,963 to $5,327

Onchain tokenized gold (PAXG, XAUT, CACHE, AWG, PMGT on Ethereum) grew its combined circulating supply from ~687K troy oz in March 2025 to over 1.3M troy oz by March 2026, a ~90% increase over 12 months. Over the same period, the gold spot price rose from $2,963 to $5,327 (+80%), with a clear supply acceleration starting in August 2025 as gold broke new highs.

Notably, supply growth outpaced price appreciation, suggesting investors were actively minting new tokenized gold rather than simply riding the price rally. Tokenized gold appears to be evolving from a niche wrapper into a blockchain-integrated store of value and macro hedge.

RWA Use in DeFi

Meta | Website | Dashboard

Only 11.8% of RWA-Backed Stablecoins are Actually Used in DeFi

According to DeFiLlama, there is $8.49B in active RWA-backed stablecoin supply, but only $1B (11.8%) is deployed across DeFi protocols.

By RWA-backed stablecoin market cap, DAI dominates with 53% ($4.48B), followed by Ondo’s USDY (15%, $1.26B) and YLDS (7%, $598M). Yet when filtering for RWA-backed stablecoins actively used in DeFi, the picture flips. USDY collapses to just 1.99% of RWA-backed stablecoin usage in DeFi and YLDS vanishes entirely. Meanwhile, USDtb and reUSD surge to 24.6% and 10.85%, respectively.

The reason is straightforward: access restrictions. Permissioned tokens that require KYC, whitelisting, or holder limitations cannot integrate seamlessly with permissionless DeFi contracts, so their onchain utilization can drop to zero. As a result, USDY and YLDS, worth a combined $1.86B, virtually disappear from the active DeFi TVL view. In contrast, permissionless assets show meaningful DeFi utilization: 96.7% of reUSD, 39.1% of USDai, 29.5% of USDtb, and 28.0% of legacy FRAX.

Zooming out, the picture is clear: $7.49B, roughly 88% of RWA-backed stablecoin supply, remains outside DeFi. Composability is limited when access restrictions meet permissionless infrastructure.

Closing Thoughts

Institutional capital is putting assets onchain, and DeFi protocols are developing ways to put those assets to work, but the real challenge lies in creating true capital efficiency once those assets land onchain.

Without active integration with DeFi, RWAs risk becoming little more than mirrored ledgers; transparent, but idle. The next phase of growth will hinge on designing mechanisms that connect these tokenized assets to onchain liquidity, credit, and governance layers.

Further, as RWA markets mature, so must the frameworks used to analyze them. Traditional asset labels, while widely used, can be incomplete. Once tokenized, these assets carry two additional layers of risk beyond simple exposure: the risk of the digital asset issuer, and the risk of the blockchain infrastructure. Ignoring these layers can lead to an incomplete assessment of a tokenized asset’s true risk profile.

What We're Watching

• Allocation Vaults: Primer for Institutional Asset Managers

• The tokenized gold market when the US-Iran war broke out

• Long Live RWA. RWA is dead.

• New DeFi Llama dashboard tracking RWAs actively deployed in DeFi

• Dune MCP

Next Week

For Nexus’ next issue, we turn to Perpetual DEXs, exploring how decentralized derivatives infrastructure is maturing and what that means for onchain market structure.