Let me explain.

Crypto buybacks are really a burn mechanism

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Projects “spent” $638 million year to date in 2026 on buybacks.

A typical crypto buyback routes protocol revenue into buying its token, then burns or permanently removes those tokens from circulation.

The protocol team does not keep what it buys. The benefit flows to remaining token holders through lower supply.

Tokens continuously enter circulation through staking rewards, incentives, and unlocks. Buybacks work in the opposite direction by removing supply. In that sense, they are closer to Ethereum burning transaction fees than a public company buying back stock.

A public company first earns and retains cash, then chooses whether to reinvest it, make an acquisition, pay a dividend, or repurchase shares. Those shares can also be held as treasury stock and potentially reissued.

A public company buyback is an active capital-allocation decision and can signal conviction.

The price support from open-market buybacks is less than 2.5%, smaller than the headline numbers suggest.

HYPE and PUMP, the two largest programs we analyzed, currently represent less than 2.5% of their tokens’ trading volume. Even at PUMP’s peak, buybacks reached about 11%.

The buying provides temporary support, but most of the benefit comes from the burn.

Crypto buybacks are ultimately closer to traditional token burns than a signal of team conviction.

The big picture: Trump says the CFTC is working to bring Hyperliquid to the U.S. legally.

Why it matters: Hyperliquid isn’t just crypto anymore. Equities, commodities, and pre-IPOs now drive more than half its volume.

What’s next: U.S. access could bring millions of traders, plus more issuers, brokers, market makers, and infrastructure providers.

The bottom line: Live, 24/7 Hyperliquid data is becoming essential for serious traders.

By the numbers:

Current Unitree pre-IPO market:

• $94/share, implies a $38B valuation

• $66M in volume traded

• 3,768 wallets traded

• $10.4M open interest

As open interest grew to $10.4M, price rose with it while funding remained relatively flat. The market appears to have converged around a stable, broadly agreed valuation, 4x the offer price.

On a per wallet basis:

• Three wallets hold more than $1M each, all long totaling $4.7M

  • entered at $89 to $93

• One $1.6M short at 10x leverage

• Positions under $50K are 75% short by open interest

A large deviation from $94 would force a meaningful amount of positioning out. If price were to change to:

• $45, 2x offer price: 33% of longs liquidated

• $128, 5.7x offer price (like the CXMT IPO): 46% of shorts liquidated

So how much weight should we actually put on Hyperliquid’s $94 price?

The historical record is mixed.

The earliest markets were much less consistent. Cerebras’ Hyperliquid price sat 24.2% below its eventual open, while Quantinuum’s sat 40.4% above.

Then came SpaceX. It attracted $1.0B of volume and more than 29,000 traders, and ultimately priced the open within 3.6%.

But volume alone does not explain the improvement.

CXMT traded only $206M, roughly one-fifth of SpaceX volume, yet still came within 2.5% of its opening print, at the bell. It also had only about 3x Cerebras’ volume, while producing dramatically better accuracy.

What changed was not just liquidity. The market itself matured.

SpaceX brought far more attention to pre-IPO perpetuals and attracted participants willing to research, trade and arbitrage these markets. CXMT suggests that once those participants are present, price discovery can remain strong even without SpaceX-level volume.

Trader count reinforces that point. SpaceX had 29,041 traders and CXMT 7,778, compared with 3,618 for Cerebras and 1,781 for Quantinuum.

That makes Unitree particularly interesting.

Unitree Currently has $10.4M in open interest, $66M of volume and 3,768 traders, putting it relatively close to Cerebras on headline activity. But it is launching several months later, into a market that has already successfully priced SpaceX and CXMT.

My suspicion is that recency of listing may matter almost as much as volume. As these markets become better known, they attract more informed participants, arbitrage capital and attention, which should make the signal progressively harder to ignore.

We will grade the $94 estimate against Unitree’s first Shanghai trade and publish the result.

Initial Unitree report from Friday: here

All figures from Allium’s Hyperliquid dataset to 16 August 18:00 UTC, both Unitree markets, single-counted. Open interest stated one-sided; the venue’s displayed figure is two-sided and roughly double. Precedent open interest measured in the final hour before each stock’s first trade; opening prints press-sourced; first trades measured from the tape. IPO price ¥150.80 at USD/CNH 6.7408. Informational only. Not investment advice.–––––

At first, I was skeptical.

How could Polymarket, one of the most innovative companies in crypto and arguably the most promising consumer use case, lose its foothold in prediction markets?

But any way you cut the data, Kalshi is now leading.

Polymarket went from 88% of prediction-market volume in 2024 to 28% in 2026 without getting smaller. Kalshi simply grew much faster.

So what happened?

I think there are three factors we need to consider: parlays, Robinhood and regulation.

Today, we will focus on parlays. Stay tuned for parts two and three.

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Kalshi turned prediction markets into a sportsbook

Sports became Kalshi’s largest category, generating $19.0 billion of notional volume in July.

Political and economic markets often remain open for weeks or months. Sports markets can open, trade and resolve within a single day. The same capital can therefore move through several markets instead of remaining committed to one longer-term outcome.

This helps explain one of the largest differences between the two venues. Polymarket’s capital sits for longer. Kalshi’s turns over more frequently.

Kalshi’s rapid turnover created the ideal foundation for parlays.

Kalshi made parlays effectively unlimited

Kalshi’s second-largest category is “combos,” its version of parlays.

Users can combine existing markets into a single outcome, such as Bitcoin, Ether and MicroStrategy all rising, or the Raptors, Blue Jays and Maple Leafs all winning.

The combination is sent to market makers through a request for quote. A market maker prices and creates the market, which can then trade like any other contract.

This lets Kalshi offer millions of user-generated combinations without listing each one manually.

In July 2026, Kalshi traded nearly 9.9 million distinct parlay markets versus roughly 439,000 single markets. Polymarket, which manually lists combos, had 188, only 30 of which traded that month.

Kalshi parlays generated $14.98 billion of notional volume in July, or 36% of total volume, making combos its second-largest category behind sports.

But that notional figure requires context.

Parlays represented only 12% of the cash actually staked and 17% of Kalshi’s fees. For every dollar of parlay face value traded, users committed approximately 10.7 cents in cash. In contrast, a dollar of single-market notional carried approximately 44.7 cents.

Many multi-leg outcomes trade at very low probabilities. A contract with a $1 payout may cost only a few cents, but the full $1 still appears in notional volume. However, even after removing the parlay category, Kalshi remains ahead.

Every parlay may create several additional hedging trades

There is another potential amplification layer that exchange trade data cannot measure directly which is market-maker hedging.

If a user buys a parlay on the Raptors, Blue Jays and Maple Leafs all winning, the market maker selling it takes exposure to all three outcomes and may hedge in the underlying markets.

One user trade can therefore generate multiple layers of activity: the combo itself, the market maker’s hedge trades, and later hedge adjustments as prices move.

That activity is real, not artificial. But it means a single piece of end-user demand can generate considerably more volume, open interest and fees than a straightforward single-market trade.

The caveat is that we cannot observe how much of this hedging occurs, where it is executed or what incentives market makers receive. Our fee estimates, which apply Kalshi’s published fee schedule to trading activity, should therefore be treated as an upper-bound estimate of gross fees rather than confirmed net revenue.

Still, some mechanical amplification is likely: one combo creates a new market and may trigger several additional hedge trades.

Stay tuned for Part II, where we explore how prediction markets are on track to generate $2.65B in revenue this year, and why Kalshi’s largest distribution channel, Robinhood, could also become its biggest competitive threat.

Data from Allium, covering Kalshi, Polymarket and Polymarket US. Fees are calculated using each venue’s published fee schedule. Robinhood figures are based on its second-quarter 2026 results. Whether firms quoting combo markets hedge the individual legs, and where those hedges occur, is not visible in exchange trade data.

That makes Circle’s earnings relatively straightforward to understand.

Two variables matter most:

1. How much USDC is in circulation.

2. What yield Circle earns on the reserves.

We estimated that Circle would generate $667.4 million of reserve income in Q2

Circle reported $667.7 million.

The estimate missed by roughly $330,000. That accuracy came from combining Allium’s adjusted circulating-supply methodology and Coinbase wallet labels to identify the share of reserve income attributable to Coinbase.

As of August 4, USDC in circulation is $71.8 billion

$7.4 billion below USDC March peak and another $1.3 billion below June 30 (Q2 end).

That means Circle entered Q3 with a meaningfully smaller reserve balance than it carried through most of Q2.

Monetary policy which currently has a 50% odd of a rate hike in September could help Q4’26 revenues

At the current USDC balance, a 25-basis-point increase in reserve yields would add approximately $44 million of quarterly reserve income.

A reliance on rate hikes creates an unusual dynamic for Circle.

Higher rates increase Circle’s reserve yield, but they can also reduce crypto trading demand and shrink the USDC balance earning that yield.

USDC depends more on trading than payments

Circle often presents USDC as infrastructure for global payments.

That may be the long-term opportunity, but it is not yet the primary driver of USDC and stablecoin activity in general.

Trading represented approximately half of Allium-measured organic USDC volume during the first half of 2026. Total organic USDC volume reached $159 billion, compared with $1.31 trillion for USDT.

Tron, which primarily hosts USDT, accounts for 71% of all stablecoin payment volume measured by Allium.

USDC has genuine payment adoption, and Circle reported that the Circle Payments Network reached a $14.7 billion annualized transaction run rate at the end of Q2, up 76% quarter over quarter. But that remains small relative to the supply and activity associated with crypto markets.

Circle’s fastest-growing product may compete with USDC

Circle is also expanding USYC, its tokenized Treasury fund.

USYC reached approximately $3.0 billion of assets. It now represents roughly one-fifth of a tokenized U.S. Treasury fund market that has grown more than 7x in two years.

USYC is available to institutions only and its economics are far less attractive than USDC’s. Circle retains roughly 0.37% on each dollar held in USYC, compared with about 2% on USDC, because most of the Treasury yield is passed to USYC holders. That means USYC may grow Circle’s addressable market while also competing with USDC for capital used in trading, collateral and store-of-value activity. As tokenized Treasury funds become easier to use in DeFi, investors may increasingly prefer an onchain dollar product that passes through the yield rather than a stablecoin that keeps it.

Full report: link

Circle reported $667.7 million of Q2 reserve income against Allium’s pre-earnings estimate of $667.4 million. Allium’s Q3 figures are run-rate estimates based on observed USDC supply and reserve yields, not earnings guidance or investment advice.

1. Did the liquidation event on Hyperliquid move SK Hynix’s share price?

2. More importantly, what does this imply about the emerging two-way pattern between traditional and crypto markets?

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If you’re not familiar, here’s what happened:

At 23:00 UTC on 27 July 2026, the price feed behind SK Hynix’s perpetual futures contract on Hyperliquid printed $890.14. A minute later it printed $872.25, against $1,131.40 the minute before. By 23:02 it was back at $1,144.80, above where it started1.

The excursion lasted two one-minute snapshots resulting in:

No, I don’t think the Hyperliquid event materially affected SK Hynix’s regular trading session or pushed the stock lower afterward.

Because the perpetual is cash settled, trading on Hyperliquid does not directly buy or sell SK Hynix shares. Any effect on the stock would have to come indirectly through sentiment or trading activity carrying into the Seoul market, and there is no clear evidence that happened here.

Hyperliquid traders also did not accept the bad tick as the true price.

Their orders stayed much closer to the stock’s price immediately before the bad price tick, but the margin system still used the imported price and triggered the liquidations. During Tuesday’s session, Hyperliquid’s price also stayed slightly above the Seoul price and never below it. If crypto selling had been pulling the shares down, we would expect the opposite.

The broader move looked more like a repricing of memory stocks.

SK Hynix fell about 18% across Tuesday and Wednesday, while Micron fell 14% and the Roundhill Memory ETF fell 15%, despite neither having a comparable event on Hyperliquid. Nvidia and TSMC fell closer to 5%.

That said, major liquidations may matter more as 24/7 markets grow.

As Hyperliquid and similar venues add stocks from South Korea, Japan, China, Europe and elsewhere, global traders can build large positions while local exchanges are closed. Those positions can shape sentiment when the market reopens, while the new price action then feeds back into the 24/7 market. The Federal Reserve has described a similar two-way pattern between traditional and crypto markets, where stress can pass from one to the other and then feed back again. Over time, the two could reinforce each other and amplify a bad print, rumor or misread event before investors have time to assess what is real.

That is not what happened here. The SK Hynix event was technical. The perp imported a real trade from a thin pre-market venue and repriced leveraged positions as designed. The perp worked as intended, but the approach to selecting and handling external price sources will need to change to avoid similar anomalies.

The losses were concentrated in a handful of accounts, though most of the accounts were small.

748 of the 990 were under $10,000 and lost $339,000 between them. Fourteen accounts at $1 million or more carried 57% of the total. The median account lost about $1,000, against an average of $59,892.

Trade.xyz said it will cover liquidation losses attributable to the anomalous portion of the move, and that it is reviewing how prices are formed, “including revisiting assumptions on external venues.” Usage has not suffered, and 29 July was the contract’s busiest day since it launched, at $1.74 billion in volume, with open interest back to roughly $542 million.

As stablecoins have grown to over US$300 billion in market cap, public sector entities working to understand digital asset markets face a fundamental challenge: how do you gain visibility into assets that operate 24/7 across multiple blockchains with transaction finality measured in seconds, not days?

Digital assets operate across dozens of blockchain networks with distinct protocols and economic models, processing billions in daily stablecoin volume. The fundamental challenge lies in synthesising real-time activity across this fragmented landscape - from established networks like Ethereum to emerging Layer 2 solutions and new blockchain architectures that launch regularly. Without this holistic, cross-chain perspective, assessments may miss critical interconnections and emerging patterns spanning the entire digital asset ecosystem.

Understanding stablecoin market development requires real-time visibility into transaction flows, user activity patterns, and aggregate volumes - both domestically and globally. It requires the ability to distinguish compliant issuers from the broader market. And it requires infrastructure that can keep pace with blockchain-native settlement speeds.

Allium built a dashboard to explore this visibility gap and improve understanding of existing stablecoin activity across blockchain networks, which was showcased at the MAS Future of Finance pavilion during the Singapore FinTech Festival 2025.

What Was Built

At the Singapore FinTech Festival 2025, a stablecoin activity dashboard was showcased at the MAS Future of Finance pavilion. The dashboard demonstrates continuous visibility into the activities of a subset of stablecoins with three core capabilities:

1. Transaction Flow Analysis by Use Case

The system categorizes stablecoin transactions by economic purpose - cross-border payments, merchant settlements, remittances, treasury operations, and institutional transfers. This helps understand how stablecoins are being used within and across jurisdictions.

2. User Activity Patterns by Category

The dashboard tracks activity across user segments: retail consumers, merchants, financial institutions, and corporate treasuries. This segmentation enables understanding of adoption patterns and use case evolution across different market participants.

3. Aggregate Volume Monitoring (Global and Domestic)

The dashboard showcases the potential to view both Singapore-specific stablecoin volumes and global activity for context. This dual perspective illustrates how such infrastructure might help improve understanding of market trends and activity patterns.

Specifically, the dashboard focuses on an initial set of stablecoins that are either MiCA compliant, substantively compliant with the upcoming MAS’ single-currency stablecoin framework, or included in the NYDFS Greenlist.

Technical Infrastructure Enabling Ecosystem Transparency

Building real-time visibility infrastructure for blockchain-based assets requires solving several technical challenges that traditional financial market intelligence systems don’t face:

Multi-Chain Data Aggregation

Stablecoins operate across Ethereum, Polygon, Solana, Arbitrum, and other blockchain networks. The infrastructure must normalize data from chains with different data models, transaction structures, and finality mechanisms into a unified view.

Real-Time Processing at Scale

Blockchains produce continuous streams of transactions. The system must process, categorize, and aggregate millions of transactions in real time to provide current visibility - not yesterday’s snapshot.

Transaction Classification and Enrichment

Raw blockchain data shows wallet-to-wallet transfers. Understanding ecosystem development requires knowing what those transfers represent: Is this a merchant payment? A cross-border remittance? An exchange deposit? The infrastructure must decode smart contract interactions and enrich transactions with business context.

Compliance-First Data Filtering

Not all stablecoins meet established compliance standards. The system must identify and track only those tokens that meet specific criteria, filtering out hundreds of non-compliant or unregulated alternatives.

Verification and Data Quality Assurance

For meaningful ecosystem analysis, data accuracy is essential. The infrastructure includes continuous verification to ensure data quality and proper transaction classification.

Allium built the dashboard, leveraging its blockchain data infrastructure to make this level of visibility technically feasible - from initial ingestion through final enrichment.

Singapore’s Approach to Responsible Stablecoin Ecosystem Development

MAS has consistently taken a principles-based approach to digital asset ecosystem development. For stablecoins, this means supporting an environment where compliant issuers can operate with clarity around reserve backing, redemption rights, and operational standards.

At the baseline, MAS Digital Payment Token (DPT) regulatory framework regulates services relating to DPTs (including stablecoins) for risks relating to ML/TF, tech, consumer harm and business conduct. MAS regulatory approach towards stablecoin, is a step-up framework from the baseline DPT regime, and seeks to ensure a high degree of value stability for stablecoins regulated in Singapore. Those seeking the “MAS-regulated stablecoin” designation must meet requirements on value stability under the Single Currency Stablecoin (SCS) framework. The SCS framework finalised in the 2023 response to consultation paper currently exists as regulatory guidance that sets out strict standards for reserve backing, capital requirements, redemption processes, and transparency for high-quality stablecoins.

MAS is now working on legislative amendments to the Payment Services Act to formalise the framework. This legislative process will codify the existing 2023 framework into formal law, providing stronger legal certainty and enforcement mechanisms while maintaining the same core principles of ensuring value stability and consumer protection that distinguish regulated stablecoins from volatile crypto assets.

What Modern Stablecoin Ecosystem Infrastructure Looks Like

The dashboard demonstrates what transparency infrastructure needs to deliver for understanding blockchain-based financial instruments:

Real-time, not retrospective. Traditional quarterly reporting provides limited visibility into assets that settle instantly and operate continuously. Current data enables better understanding of ecosystem evolution.

Use case-driven, not just volume-based. Knowing that US$10 billion in stablecoins moved through a jurisdiction matters less than understanding whether those flows represent consumer payments, institutional treasury operations, or other use cases.

Cross-border in nature. Stablecoins usage can transcend geographical borders. Understanding ecosystem development requires visibility into both domestic activity and its global context.

Compliance-scoped. Attempting to track every token is neither feasible nor useful. Focus must remain on compliant, systemically relevant issuers.

Built on verified data infrastructure. Understanding ecosystem development requires trustworthy data. The underlying infrastructure should be able to support accuracy at scale.

Implications for Public Sector Entities Supporting Digital Asset Ecosystems

The dashboard demonstrates several considerations for other jurisdictions and organisations working to understand stablecoin ecosystem activity.

Assess regulatory status of the stablecoin. Build infrastructure focused on tokens meeting established standards first. Expanding to broader ecosystem monitoring is easier than trying to cover everything from day one.

Leverage specialized data infrastructure. Blockchain data infrastructure is complex and rapidly evolving. Organizations should focus on their core mandates while working with technical infrastructure providers where appropriate.

Design for real-time from the beginning. Retrofitting quarterly reporting systems for real-time visibility is harder than building with that requirement upfront.

Emphasize transaction context over raw volume. Understanding use cases, user segments, and economic flows provides more actionable insight than aggregate transaction counts.

As more jurisdictions, including the United States, European Union, and other G20 nations, develop approaches to digital asset ecosystems, the need for transparent, real-time visibility infrastructure continues to evolve. The showcase at the Singapore FinTech Festival demonstrates that building such infrastructure is technically feasible and could provide operational value for improving understanding of stablecoin activity and market dynamics.

Disclaimer: The dashboard was showcased at the MAS Future of Finance pavilion during the 10^th Singapore FinTech Festival to demonstrate the infrastructure needed for understanding stablecoin ecosystem activity. Allium provided the blockchain data infrastructure enabling real-time multi-chain data aggregation, transaction enrichment, and compliance-focused filtering. The dashboard does not reflect MAS’ views on what constitutes or will constitute a regulated stablecoin, either currently or in future regulatory determinations.

The reason is straightforward: issuing a stablecoin is now table stakes. The technology is proven, regulatory frameworks are maturing, and infrastructure providers have made launch processes relatively simple. Distribution and liquidity—not issuance—determine which stablecoins succeed.

Building real adoption requires understanding what’s actually happening onchain: where your token flows, who holds it, which use cases drive volume, and how you compare to competitors. Without accurate onchain intelligence, issuers are operating blind.

Why Onchain Data Infrastructure Matters for Issuers

Stablecoin issuers face three fundamental challenges once their token launches:

1. Institutions require auditable metrics. Major allocators won’t commit capital to a stablecoin without reliable data for risk management and compliance reporting. If your supply and volume numbers can’t be verified, institutional adoption stalls.

2. GTM strategy requires granular visibility. Effective go-to-market means knowing where liquidity concentrates, which protocols drive usage, who your largest holders are, and which chains show momentum. Public, community-maintained dashboards showing total supply don’t provide this level of insight.

3. Analytics platforms show inconsistent numbers. Most providers aggregate data from multiple sources, leading to discrepancies in reported supply, volume, and holder counts. When your internal metrics don’t match what third parties report, explaining performance to stakeholders becomes difficult.

The result: issuers can’t optimize distribution strategy, can’t hold liquidity partners accountable, and can’t benchmark performance accurately. This makes the difference between a stablecoin that gains traction and one that joins the long tail of unused tokens.

Three Core Capabilities Stablecoin Issuers Need

Building effective onchain intelligence starts with three foundational capabilities:

1. Balance & Holder Monitoring

What it tracks: Historical balances at hourly or daily granularity across all chains where your stablecoin operates. This includes current holder distribution, concentration metrics (what percentage of supply the top 100 wallets control), and wallet-level activity patterns.

Why it matters: Understanding holder composition reveals adoption patterns. Are your tokens concentrated in a few large wallets or distributed broadly? Are new holders entering the ecosystem or is growth stagnant? Which wallets are most active, and which are dormant?

What it enables:

• Operational monitoring for compliance and risk management

• GTM targeting—identify whales to convert, active users to engage, and dormant holders to reactivate

• Strategic decisions about where to focus liquidity incentives or partnership efforts

2. Accurate Circulating Supply Tracking

What it tracks: Circulating supply that filters out noise from foundation treasuries, pre-minting addresses, and burned tokens. This provides a clear view of how much of your stablecoin is actually in market circulation across different chains and ecosystems.

Why it matters: Total supply metrics are misleading. If your foundation holds 60% of minted tokens in a treasury wallet, that inflates your apparent market presence. Accurate circulating supply shows real market share and enables meaningful comparisons with competitors.

For multi-chain stablecoins, this becomes critical: seeing which chains drive actual adoption versus which show inflated supply helps prioritize where to invest in ecosystem development.

What it enables:

• Strategic decisions about which chains and ecosystems to prioritize

• Accurate benchmarking against competitors (apples-to-apples comparisons)

• Credible public reporting that builds institutional confidence

3. Enriched Transfer Activity

What it tracks: Stablecoin transfers labeled by economic context—is this a CEX deposit, a DEX swap, a lending protocol interaction, a bridge transaction, or a peer-to-peer transfer? Includes filters to identify and exclude wash trading or circular volume that inflates usage metrics.

Why it matters: Raw transfer volume doesn’t distinguish between meaningful economic activity and noise. A million dollars in volume from genuine DEX trading represents real adoption. A million dollars from wash trading or internal protocol movements does not.

Understanding which use cases drive real volume—cross-border payments, DeFi trading, treasury operations, merchant settlements—reveals where your stablecoin has product-market fit and where GTM efforts should focus.

What it enables:

• GTM strategy informed by actual usage patterns (which verticals and protocols to prioritize)

• Liquidity partner accountability (verify market makers are performing as expected)

• Competitive intelligence (how does your usage profile compare to established stablecoins)

What Good Onchain Intelligence Enables

When issuers have access to these three capabilities, several strategic advantages follow:

Build institutional trust. Public dashboards showing auditable, verified metrics demonstrate transparency. Institutions evaluating your stablecoin can verify supply claims, track usage trends, and assess market adoption independently. This credibility accelerates institutional onboarding.

Optimize GTM investment. Rather than spreading resources across all possible integrations, focus on protocols, chains, and user segments where data shows momentum. If one chain shows 10x the transfer activity of another, that signals where to prioritize partnerships and liquidity incentives.

Manage liquidity partners. Market makers and liquidity providers commit to maintaining depth and tight spreads. Tracking their performance across venues—order book depth, slippage, fill rates—ensures they deliver on commitments. Data makes these relationships accountable.

Benchmark competitive position. Understanding your market share across chains, your adoption velocity relative to competitors, and where you’re gaining or losing ground informs strategic decisions. Are you winning on Layer 2s but losing on Solana? The data tells you where to adjust strategy.

How USDH Built Public Transparency into Their Launch Strategy

Native Markets launched USDH with a public dashboard built on Allium’s data infrastructure.

The dashboard provides real-time transparency into USDH supply across HyperEVM and HyperCore, holder distribution metrics (total active addresses, median and average balances), top holder identification, and spot market volumes showing USDH’s market share against other stablecoins. Anyone—users, institutions, or partners—can verify USDH’s adoption metrics independently.

Explore the USDH dashboard →

Start Building Your Onchain Analytics Strategy

The stablecoin market will continue growing more competitive. Regulatory clarity and improved infrastructure mean more issuers will launch tokens targeting specific use cases, geographies, or customer segments. Success won’t come from having the best reserves or compliance framework alone—those become table stakes.

Winners will combine strong distribution strategies with data infrastructure that shows what’s working. This means starting with the three core capabilities outlined above: balance and holder monitoring to understand your user base, accurate circulating supply to benchmark market position, and enriched transfer activity to see which use cases drive real adoption.

For issuers launching new stablecoins or scaling existing ones, investing in onchain intelligence infrastructure early creates compounding advantages. The sooner you understand adoption patterns, the faster you can optimize distribution—and the wider the gap between you and competitors still operating blind.

Learn more about how leading stablecoin issuers use onchain data infrastructure: allium.so

Explore fiat-backed stablecoins at Visa Onchain Analytics x Allium

Explore the USDH dashboard built with Allium