Since 2023, RWA has evolved from a concept to a track supported by real-world data.

Tokenization of U.S. Treasuries, gold, on-chain private credit, a series of products have emerged, and TVL has grown rapidly. BlackRock's BUIDL Fund has been live on Ethereum for less than a year, with assets under management surpassing $500 million; Franklin Templeton has brought its money market fund to Polygon and Stellar, crossing this threshold as well. Boston Consulting Group predicts that the asset tokenization size will reach $16 trillion by the 2030s. This number is impressive enough, but more worthy of attention is the structural premise behind it, whether this track can carry assets of this magnitude and operate securely for a long enough time.

Most RWA teams have grappled with the same issue: What assets can go on-chain? How to migrate on-chain?

The answer to this question has already been market-proven. Government bonds can go on-chain, gold can go on-chain, private credit can go on-chain, and real estate, commodities, and even carbon credits have successively witnessed experiments and products of tokenization. At a technical level, minting a token representing asset ownership is not a high barrier; after running through a set of standard processes involving smart contracts, custodial accounts, and on-chain oracle price feeds, the product can go live. The industry spent about two to three years refining the answer to this question: almost any asset with clear ownership and legal definability can be tokenized.

However, immediately afterward, RWA teams faced the next question: after moving on-chain, how to ensure that the assets can operate on-chain for long enough while still maintaining an undistorted economic relationship between the token and the underlying asset?

FRS, a New Solution Proposed by Matrixdock

Under this issue, Matrixdock has proposed the FRS (Fungible Reserve Standard), attempting to address the on-chain holding cost issue from a mechanistic perspective.

Matrixdock is a leading Asia-based institutional-grade RWA tokenization platform, affiliated with BIT (formerly Matrixport), whose products include the STBT U.S. Treasury token, XAUm gold token, and XAGm silver token. Over the past few years, Matrixdock has accumulated comprehensive practical experience in institutional-grade RWA, ranging from compliant custody, on-chain transparency to DeFi integration. It is also the core technical partner for the tokenization of sovereign assets in the Kingdom of Bhutan, building the TER gold token for GMC.

As mentioned earlier, physical assets on-chain exist in reserves, incurring custody fees, insurance fees, audit fees annually, but in most tokenization designs, these expenditures are entirely invisible. Tokens claim to represent an ounce of silver, as time passes, the actual amount users can redeem is less than an ounce, but users cannot instantly learn about this on-chain.

The correspondence between the token and the underlying reserve has been static since issuance, with any subsequent changes maintained through off-chain disclosures by the issuer. This issue accumulates over time. Perhaps a one-year deviation is still acceptable, but what about the third year or the fifth year? For products without an automatic correction mechanism, the longer they operate, the greater the discrepancy between on-chain tokens and the underlying assets.

FRS's solution to this issue is to introduce a variable q(t), representing the quantity of underlying real-world assets each token corresponds to at time t.

How to Reflect Asset Cost

A specific analysis of FRS's basic formula is: q(t) = q(0) × (1 - r/365)^t

Where q(0) refers to the initial corresponding asset amount per token, which was 1 troy ounce of silver when XAGm was issued;

r refers to the annual holding cost rate, which is 0.3% for XAGm (= 0.003);

and t represents the number of days elapsed since issuance;

Traditional RWA products handle holding costs in only two ways: periodically withdrawing assets from the vault for payment or creating separate contracts to charge users individually. The former disrupts the 1:1 correspondence between the reserve and the token, while the latter is incompatible with DeFi's composability.

FRS's approach is to leave the assets in the vault untouched and only adjust q(t). Each day, q(t) decreases by r/365, with the quantity of assets per token decreasing slightly every day in user wallets. The portion of the "shrinking" assets represents the custody cost transparently recorded on-chain. There are no off-chain operations, no manual intervention, just automatic operation according to the formula.

How to Handle Long-Term Supply Changes

The reserve relationship equation requires precise adherence at all times, meaning that every new minting and redemption transaction must be completed within this framework without exception.

When new assets enter the reserve, the quantity of newly minted tokens is determined by the current q(t): New token amount = New asset amount / q(current). When users redeem, the corresponding tokens are burned, and the reserve decreases accordingly. The entire process is automatically executed on-chain logic, without manual calculation or time lags from batch settlements. The reserve relationship equation is reestablished at the completion of each transaction.

The true test of this mechanism will only be seen over time. Traditional RWA products have a common structural flaw: on-chain deviations accumulate continuously over operational time. The error in the first year is about 0.5%, which may have reached 1.5% by the third year.

The longer the time, the more blurred the economic relationship between the token and the underlying asset becomes. FRS answers this question with a different logic: by daily automatic decay of q(t), the deviation is continuously brought back to zero. It does not calibrate periodically, but reflects precisely every day. In theory, a product based on FRS can run indefinitely, and on-chain economic relationships will not distort over time.

There is another design detail worth mentioning separately. FRS explicitly separates custodial costs from management profits: the r in the formula only reflects actual holding costs incurred, such as storage, insurance, and audits, without including any management fees or profit extraction. This boundary is intentional—it aims to make the token a mirror of the economic authenticity of the underlying asset, rather than a financial product embedded with business profits. The transparency of costs is close to the disclosure level of commodity ETFs but entirely on-chain verifiable, not relying on any party's active disclosure.

This is the most fundamental difference at the structural level between FRS and most existing RWA products: not doing better but doing a different thing. The former treats the holding cost as an off-chain financial issue, while the latter solves it as an on-chain mechanism problem.

How Does Silver XAGm Work?

Establishing the FRS framework in a whitepaper is one thing, but running stably under real assets and real market pressure is another.

So we can understand the role of FRS in the real market by analyzing Matrixdock's latest product, the Silver token XAGm.

Why use silver as a case study? Not because silver is easy but precisely because it is not easy.

In precious metals, the logic of gold is relatively straightforward: it is a macro reserve asset, and its price is mainly driven by safe-haven demand and central bank behavior, with relatively predictable volatility, sufficient market depth, and a mature custody system. The difficulty of tokenizing gold mainly comes from compliance and custody, as the properties of the asset itself are stable.

But silver is different. Silver is simultaneously driven by two completely different pricing logics: one is an investment logic, where silver serves as a hedge in precious metals, following gold's macro narrative; the other is an industrial logic, as silver is a core raw material for solar panels, electric vehicles, 5G base stations, AI hardware, directly tied to the global manufacturing cycle. These two logics sometimes align, sometimes hedge, and sometimes amplify each other.

The result is that silver's price volatility has historically been about two to three times that of gold.

It rises more sharply in a bull market, falls more deeply in a bear market, and experiences more severe liquidity contraction under extreme market pressure. Silver has a nickname circulating in the financial industry: the "poor man's gold." Behind this nickname is its much lower unit price, much larger physical volume, and much higher price elasticity compared to gold.

These characteristics make silver more demanding in terms of on-chain structure compared to gold.

Firstly, this means that the holding cost of silver is higher within the precious metals spectrum. The reason is quite straightforward: the unit value of silver is much lower than that of gold, but its physical volume is much larger. For the same market value, silver's volume is approximately 80 times that of gold. This implies that in terms of storage space, transportation costs, and insurance rates calculated based on volume rather than value, silver has to bear a higher proportion.

Moreover, the high volatility of the silver price poses additional requirements for RWA token structures. When the price of the underlying asset fluctuates significantly, holders will inquire: how much silver does the token I hold correspond to right now? If the answer relies on off-chain disclosures, during moments of intense market fluctuation, the credibility of this answer would be greatly compromised. Not because the issuer is dishonest, but because "trust" itself takes time, and the market does not offer that time.

FRS's value here lies in resolving this trust issue mathematically.

Using XAGm's 0.3% annualized fee rate as an example: the daily decay rate is approximately 0.000822%, and after holding for a full year, q(365) = 0.997 troy ounces. The cost does not disappear into thin air; it is precisely encoded into time.

Currently, the current q(t) value can be directly queried on-chain: 0.999589042. This number represents the cumulative record of holding costs every day since the product went live.

We can verify whether the entire mechanism is self-consistent with real-time data:

Circulating supply: 45,972.892 XAGm tokens;

Silver reserve: 45,954.000 troy ounces;

Current q(t): 0.999589042;

Verification: 45,972.892 × 0.999589042 ≈ 45,954

Deriving the days since launch from q(t): approximately 50 days, perfectly matching the product release date. The data is on-chain, the logic is in the contract, and anyone can independently verify.

The formula is public, the contract is public, and the reserve data is on-chain. This feature's value is amplified in high-volatility assets such as silver.

If FRS can operate stably with silver, maintain the reserve relationship equation undistorted under extreme market conditions, and ensure the automatic decay of q(t) functions normally under liquidity pressure, then as a scalable design paradigm, it possesses greater persuasiveness.

The current market cap of XAGm is approximately $3.95 million, with a circulating supply of around 46,000 ounces. However, scale has never been the core indicator at this stage. What needs to be proven at this stage is the stability of the mechanism under real asset and real market conditions. Silver's high volatility, in fact, provides a more stressful testing environment than gold.

Beyond the structural design, there is also a practical issue: how to ensure the off-chain physical reserves are consistent with on-chain data?

This is a foundational trust issue that RWA products commonly face. The FRS itself cannot solve it, but XAGm has established an independent verification mechanism at this level.

On the physical level, XAGm's underlying silver is held in an institutional-grade vault, in the form of silver bars that meet the LBMA Good Delivery standard. The silver undergoes regular independent physical audits by Bureau Veritas, with audit reports publicly available. Bureau Veritas is a globally recognized third-party inspection and certification organization, with no conflict of interest between them and the issuer.

On the on-chain level, Matrixdock has implemented a Proof of Reserves mechanism, where the circulating supply, q(t) value, and total underlying silver supply are dynamically verifiable. Anyone can independently verify through a formula whether the relationship between these three factors holds true.

What if the custodian encounters issues? XAGm employs a bankruptcy remote structure, where the underlying physical assets are held by a separate legal entity, distinct from Matrixdock's operating entity. This means that even if the issuer faces operational problems, the underlying reserves remain legally owned by the holders and are not subject to commingling.

It should be noted that the mechanisms above provide structural safeguards rather than risk-free guarantees. Off-chain audits have time intervals, the accuracy of on-chain data relies on oracle reliability, and both the custodian and auditor themselves carry operational risks. These are systemic constraints that any tokenized real asset product cannot entirely eliminate. The contribution of FRS lies in achieving a level of on-chain transparency that is independently verifiable, rather than claiming to have resolved all risks.

Post-FRS, how far will Matrixdock go?

Of course, these use cases are still in their early stages. XAGm has been live for fifty days, with a modest scale, and ecosystem integration is still underway.

In fact, XAGm itself is just a validation point; it aims to prove a problem much larger than silver.

In its Outlook 2026, Matrixdock poses a judgment: the core issue of RWA is shifting from "can it be put on-chain" to "can these assets be included in an institution's balance sheet and sustainably operate across different market cycles."

This judgment is worth our contemplation. After all, the Balance Sheet is the strictest threshold for institutions to hold assets, requiring the value of assets to be clear, accountable, and auditable at any time. An RWA product with hidden costs and a distorted economic relationship between the token and the underlying asset over time cannot enter the Balance Sheet; it can only remain at the speculative allocation level.

This means that RWA is no longer just an issuance issue but is closer to a structural issue. While many assets can be put on-chain, assets that institutions can hold long-term must maintain a stable economic relationship over time dimension, along with transparency and verifiability.

From this perspective, FRS is not just a product mechanism but a structural design that enables on-chain assets to have the "ability to enter the Balance Sheet." It addresses not the minting issue but whether assets on-chain can withstand the test of time audit.

If this direction is established, the evolution of FRS may unfold in several directions.

First is the multi-asset unified standard. Precious metals, commodities, infrastructure assets adopting the same q(t) structure, allowing DeFi protocols to use the same logic to handle different types of collateral. A lending protocol that integrates a valuation module that understands the q(t) logic can theoretically directly handle any RWA asset designed based on FRS without the need to develop custom logic for each asset separately. Standardized value will be greatly amplified here.

Second is the adjustable fee mechanism. The current FRS's r is a hardened contract parameter that ensures determinism but sacrifices adaptability. In reality, custody costs will vary with market conditions—vault rentals will increase, insurance rates will fluctuate, audit costs will evolve with compliance requirements. In the future, an on-chain governance mechanism may be introduced to make r adjustable within a certain range, but the adjustment itself will remain transparent, on-chain verifiable, rather than a unilateral decision by the issuer.

Third is cross-chain consistency. XAGm is currently deployed on Ethereum, with multi-chain extension in the roadmap. Maintaining precise synchronization of the same q(t) state in a multi-chain environment is the next engineering challenge - once even a slight inconsistency in q(t) on different chains occurs, arbitrage opportunities will arise, undermining the strict enforcement of the reserve relationship equation.

This also implies that perhaps the next round of competition for RWA will not take place at the issuance level but at the structural level.

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