Rethinking RWA: How Long Turned Stocks into Liquidity for the Robinhood Ecosystem

Stocks as liquidity

On July 14, 2026, Long launched markets where memecoins trade directly against tokenized stocks. These pairs can be loosely described as MEME/STOCK. Instead of ETH or a stablecoin, the settlement asset becomes, for example, NVDA, AAPL, or TSLA.

We covered the core mechanics of these pools and the broader narrative in detail in an overview article.

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Long’s liquidity and trading volumes grew rapidly:

• July 23 — cumulative volume in tokenized stocks exceeded $32 million, and the platform’s markets accounted for about 40% of tokenized NVIDIA volume
• August 29 — Long’s cumulative volume in tokenized stocks exceeded $210 million. About 10% of all Robinhood Chain tokenized stock liquidity was in Long pools
• September 2 — daily trading volume topped $425 million, and locked liquidity in tokenized stocks reached roughly $12 million. Cumulative AI/NVDA volume exceeded $110 million;
• September 7 — Long reported more than $1 billion in cumulative volume. The team estimates its markets accounted for around 15% of all tokenized stock volume on decentralized exchanges since the launch of Robinhood Chain, while its share of total tokenized stock liquidity was about 10%.

By September 25, according to an estimate from Kairos Research co-founder Ian Unsworth, Long held about $14 million of roughly $170 million in tokenized stocks in the Robinhood ecosystem — around 8.2%.

The main reason for the rapid growth is the pool architecture.

For example, in AI/NVDA, the tokenized NVIDIA stock serves as the real reserve asset of the automated market maker (AMM) pool. To increase market depth, liquidity providers need additional NVDA supply. This means the tokenized stock becomes not only a trading instrument, but also liquidity for other markets. 

This creates a “liquidity magnet” effect: the memecoin generates trading activity, while tokenized stocks settle into pools, enabling larger trades, routing, and arbitrage.

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Long flywheel

In Long’s materials, the liquidity flywheel is described as a sequential cycle. Its core components are:

• market depth. The more tokenized shares are concentrated in AI/NVDA, the less impact large trades have on price, and the lower the slippage
• turnover. A deeper pool enables larger trades with less slippage and makes routing and arbitrage more efficient, so it attracts more trading activity
• fees. Additional turnover generates fees for liquidity providers, and part of those funds can be routed back into the pool.

Together, these elements create a closed loop — liquidity increases market depth, depth supports turnover, and fees provide the resources for further expansion.

The connective tissue of the entire system is arbitrage. For example, the AI/NVDA market does not exist in isolation — the memecoin’s price is formed simultaneously in the pair against NVDA and in the pair against USDG. Tokenized NVIDIA also trades against USDG. Together, these markets form three linked pools:

• AI/NVDA
• AI/USDG
• NVDA/USDG.

If one of the quotes updates faster than the others, a discrepancy emerges between these routes. In that case, an arbitrageur buys the asset in the cheaper pool and sells it where the price is better, until the gap between the linked quotes narrows.

These trades add volume to multiple markets at once and generate fees for liquidity providers. Long co-founder Nate Benish calls this price linkage one of the key elements of the platform’s strategy.

A practical example of this mechanism was the team’s move on September 7: the project routed about $135,000 in accumulated NVDA-related fees back into AI/NVDA. After that, NVDA reserves within the market reached roughly $3.5 million. Available liquidity near the current price, according to Long’s data, increased by 50%.

The team also had another option — to distribute these funds among AI holders or increase the community reserve, but Long chose to grow liquidity.

Long also said it plans to automate this strategy once it has been refined. The team planned to transfer the NFT representing a liquidity provider position in Uniswap v4 to an immutable smart contract to prevent liquidity withdrawals, and to route fees back into the pool or the community reserve.

Concentration and scaling 

Until September, the “flywheel” was mostly developing around AI/NVDA under the framework described above, but on September 25, Long extended this approach to a broader network of markets by introducing LONG 500.

The new framework adds two fee distribution streams:

• 5% — to the community reserve. Part of the fee flow from tokenized stocks is routed into the AI reserve, which accumulates a share of the fee flow from these markets
• 5% — for buybacks and burns. Used to buy back and burn the community token that trades against the corresponding stock

Automatic reinvestment of liquidity provider fees remains in place. At the time of the announcement, Long said it supported more than 70 tokenized stocks, with the ultimate goal of creating a tokenized equivalent of the S&P 500. 

Under LONG 500, the platform links individual MEME/STOCK pools into a unified system — trading around different stocks increases the overall reserve, supports liquidity, and simultaneously creates demand for community tokens through buybacks.

Benish framed Long’s goal as follows: “to turn AI into a liquidity magnet, where it serves as a secondary market for the most basic underlying asset — NVDA.”

Demand driver for tokenized stocks

Growth in the inventory of tokenized stocks within Long, by itself, does not yet lead to higher demand for tokenized instruments. Assets may simply move from wallets and other venues into the platform’s pools, without increasing overall supply.

However, Unsworth examined what happens to supply after tokenized stocks flow into Long. In his estimate, the relationship looked like this:

• $1.90 in new supply of the same tokenized stock within three days for every $1 in assets absorbed by Long markets
• $2.80 — within seven days

The researcher estimated that around 20% of roughly $160 million in new tokenized stock supply could be linked to Long activity — about $32 million.

The researcher also broke down several Long markets separately:

• A Meme Coin/AMC. Before this market launched, around 113,000 AMC were in circulation. The very next day, supply approached 2.9 million. This was the sharpest jump in the sample
• BONER/HIMS. HIMS supply increased from roughly 275 to 2,400 tokens in three days. Long pools absorbed about 41% of the new issuance
• AI/NVDA. In the seven days after launch, the supply of tokenized NVIDIA rose by 158%. For the median asset over the same period, the figure was 35%

Overall, after excluding the anomalously large AMC and SPY issuances — which were noticeably larger than the other observations and heavily skewed the final result — the estimate drops to roughly $1.40 of new issuance over three days and $2 over a week for every $1 of assets locked in Long pools.

At the same time, all new tokenized stocks are issued by Robinhood Assets (Jersey) Limited. According to Robinhood, each tokenized stock in circulation is backed by the underlying share on a 1:1 basis, and the securities themselves are held with a licensed custodian. 

Therefore, issuing new tokens requires corresponding backing with underlying shares. The assumed mechanism looks like this:

• demand for MEME/STOCK increases
• the pool needs more tokenized stocks to provide liquidity
• a shortage or premium emerges on the secondary market
• opportunities arise for market makers and arbitrageurs
• an authorized participant uses Robinhood’s primary market to mint new Stock Tokens, and the new issuance must be backed by the corresponding amount of underlying shares

This is exactly the stage where demand in Long pools can turn into additional issuance — if a tokenized stock starts trading at a premium or market makers don’t have enough of it to maintain liquidity, there is an economic incentive to request additional supply via Robinhood. 

How Is Long Different From Competitors?

The MEME/STOCK concept itself is no longer unique to Long. Pons, PAIR, and Bankr also let users create markets where a new token trades against a tokenized stock. What matters more is trading scale, the amount of stock inside the pools, and the role tokenized stocks play in the platform’s economics.

Pons

Pons is, first and foremost, a mass token launch platform, where scale is defined by the number of new assets and overall trading flow. At its peak in early September, around 25,000 tokens were launched through the platform, and daily volume reached roughly $544 million. On September 3, the app also generated about $5.95 million in fees over 24 hours. By total volume and number of launches, Pons looked larger in scale, but these metrics covered all platform activity, not just tokenized stocks.

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For Pons, tokenized stocks are one of the possible settlement assets within this mass-market model. The platform has markets quoted, for example, in NVDA and SPY. However, the standalone turnover of MEME/STOCK pairs and the volume of Stock Tokens that remains inside such pools are not disclosed publicly.

Pair

Pair is the closest competitor to Long in terms of architecture. The platform uses a model of several linked pools, where a single new token can be paired with multiple Robinhood tokenized stocks at once. For a single launch, you can choose from one to five Stock Tokens, the pools run on Uniswap v4, and the initial liquidity is set up in a concentrated, single-sided format. 

As of August 31, five days after the multipool model launched, the team reported more than $26 million in cumulative volume, over 160,000 trades, more than 1,200 tokens launched, and more than $180,000 paid out to creators.

Bankr

Bankr differs from the other two competitors in that markets with tokenized stocks are embedded into a broader set of token launch tools. 

A new asset can be created via the interface, API, or a social media command, and the pairedStockAddress parameter lets you select a tokenized Robinhood stock as the settlement asset. The service documentation covers around 190 available Stock Tokens — significantly more than Long claimed in late September.

At the same time, Bankr does not position Stock Token accumulation as a standalone mechanic, and the documentation explicitly warns about low liquidity for some of the available stocks. In other words, Bankr’s strength is a broad catalog and convenient launch infrastructure, not market depth. 

The key difference with Long shows up in how tokenized stocks are concentrated within its markets. Pons, PAIR, and Bankr have no comparable public data on the share of stock supply accumulated inside their pools. Moreover, according to Unsworth, Long’s competitors’ pools, in aggregate, were returning more tokenized stocks to the market than they were absorbing. 

Risks of the new model

The more tokenized stocks are concentrated inside Long, the more noticeable its influence becomes. As scale grows, the model becomes more dependent on the quality of trading activity, liquidity, and infrastructure. Key risk factors include:

• user activity. In September, Robinhood Chain went through a sharp speculative boom. At the same time, services emerged to automate the creation of trading volume in Long pools. For example, OpenLiquid advertises such a service. As a result, it is still unclear how sustainable and organic this activity is;
• arbitrage and liquidity provider costs. Arbitrage trades increase volume and fees, but they allow the trader to profit from the automated market maker’s lagging price. This gap becomes a cost for the liquidity provider, which could deter new participants;
• Concentration. The more tokenized stocks are concentrated in a single pool or reserve, the more important this market becomes for asset allocation, and the more the ecosystem depends on its health;
• Closed traditional market. Tokenized stocks continue trading over the weekend, when the underlying shares are unavailable on regular exchanges, which affects liquidity and pricing. For example, on August 30, PAIR reported that the price of tokenized AMC during a closed traditional market temporarily diverged from the underlying share price by roughly 35 times;
• Dependence on Robinhood. Long controls secondary liquidity, but not the issuance of tokenized stocks. The issuance rules, the operation of authorized participants, and the product’s legal structure sit on the Robinhood/RHJ side. Changes to this infrastructure directly feed through to MEME/STOCK markets, because the depth of Long’s pools does not replace primary issuance.

For Long, the key phase will be the period after the first speculative boom. That is when it will become clearer how much liquidity remains in the pools and what level of turnover the market can sustain without a constant inflow of new activity.

Takeaways

Over a few months, Long has become one of the key liquidity hubs for tokenized stocks on Robinhood Chain. Its markets aggregate a meaningful share of Stock Tokens, and the platform itself has turned them from a passive exposure tool to traditional equities into liquidity for new markets — primarily memecoins.

The more Stock Tokens are concentrated within the system, the more trading volume Long’s markets can support. At the same time, demand for MEME/STOCK pairs creates additional demand for the tokenized stocks themselves, thereby expanding demand for RWA and giving them a new use case within DeFi.

How sustainable this effect is will become clearer after the current hype around Robinhood Chain cools off. If liquidity and trading volumes hold up without a constant stream of new speculative launches, that will be an argument in favor of Long’s model being sustainable.