Does tokenization improve liquidity? Short answer: not automatically. Tokenization can raise trading volume without improving liquidity. Liquidity shows up in narrower bid-ask spreads, deeper markets and lower price impact. One ECB study found tokenized bonds had about 27% lower bid-ask spreads, but research on tokenized stocks finds traditional equity markets still lead price discovery.
In mid-October 2026, The Wall Street Journal and The Block reported that nine U.S. public companies, including Broadcom, CoreWeave, Verizon, and UnitedHealth Group, had objected to tokenized versions of their shares trading on OKXICE, the joint venture between crypto exchange OKX and Intercontinental Exchange (ICE), the parent company of the New York Stock Exchange.
The timing wasn't a coincidence. Wall Street has been increasingly exploring the possibility of moving equities onchain. On September 17, 2026, the U.S. Securities and Exchange Commission (SEC) introduced a temporary "Innovation Exemption" for trading certain tokenized stocks, and one of its conditions gives issuers notice and the right to object before a venue lists a third-party tokenized version of their shares. These nine companies used that right.
So while Wall Street moves equities onchain, some of the very companies whose shares could be tokenized are pushing back. Why? OKXICE's notice did not give reasons for the objections. But they bring two fundamental questions about market structure into focus:
Does tokenization actually create incremental liquidity for traditional financial markets?
Or does it simply take existing securities, place them into another trading system, and create a parallel Wall Street, with different trading hours, participants, and order books?
These are fundamentally different economic outcomes. And distinguishing between them may be one of the most important questions facing the tokenization industry.
Why Are Companies Objecting to Tokenized Stocks?
The concerns raised so far by market participants largely fall into two categories. The first is price fragmentation. Nasdaq, which has said it will opt out of having its own shares tokenized under the SEC's framework, has argued that tokenized trading outside the national market system could drift away from the broader market on price and transparency. If the same underlying security trades across traditional exchanges and blockchain-based venues, could these markets develop different prices? More importantly, would arbitrage and market-making mechanisms be sufficient to keep those prices aligned?
The second is market quality. Applied Optoelectronics, the only one of the nine to explain its objection publicly, said it was unsure how tokenization would affect its stock price, liquidity, and volatility. Could tokenized trading have unintended consequences for the underlying stock's liquidity, volatility, and price formation?
Both concerns point to a broader question about market structure. When a new trading venue emerges, does it improve the existing market by attracting additional participants and competing for order flow? Or does it fragment liquidity across disconnected pools, making price discovery and execution less efficient?
A new venue can expand market access without necessarily improving market quality. To understand why, we need to distinguish between three concepts that are often used interchangeably: trading volume, liquidity, and price discovery.
Does More Trading Volume Mean More Liquidity?
In crypto markets, trading volume, total value locked (TVL), and token-holder counts are commonly used to measure the success of an asset. They are useful metrics. But from a market microstructure perspective, they measure very different things.
Trading Volume measures the amount of trading activity over a given period.
Market Liquidity measures how quickly and efficiently an investor can execute a transaction of a given size, with limited transaction costs, slippage, and price impact.
Price Discovery describes how new information becomes incorporated into prices and which market contributes that information first.
Higher trading volume does not automatically imply deeper liquidity. Consider a hypothetical example. Suppose a stock trades at $100 on Nasdaq. An issuer acquires $10 million worth of the underlying shares and issues an equivalent amount of tokenized securities. Those tokens subsequently trade across crypto venues. If the outstanding tokens change hands ten times in a single day, they could generate $100 million in secondary-market trading volume.
Yet the underlying equity market may have seen only the original $10 million purchase. The additional $90 million in token trading activity does not necessarily require additional purchases of the underlying stock.
$100 million in token trading volume is not the same as $100 million in new equity demand.
Nor does growth in outstanding tokenized assets, by itself, demonstrate an improvement in the liquidity of the underlying securities. In traditional market microstructure research, liquidity is more directly assessed through measures such as:
Bid-Ask Spread: The difference between the best available buying and selling prices. Narrower spreads generally indicate lower immediate execution costs.
Market Depth: The amount of liquidity available for execution within a given price range.
Price Impact: The extent to which a transaction moves the market price.
Amihud Illiquidity: The absolute price movement relative to the dollar value of trading activity.
Suppose a stock is tokenized and its traditional-market trading volume subsequently increases by 2%. If bid-ask spreads remain unchanged and market depth does not improve, we can conclude that trading activity has increased. We cannot, however, conclude that tokenization has materially improved liquidity.
The GameStop example
The 2021 GameStop episode provides a useful illustration. According to the SEC's Staff Report on Equity and Options Market Structure Conditions in Early 2021, GameStop's average daily trading volume increased from approximately 6.7 million shares in 2020 to roughly 100 million shares during the trading frenzy of January 13 to 29, 2021. That is roughly 15 times the 2020 average.
Over a broadly comparable period, Hasso et al. (2022) documented an increase in GameStop's average bid-ask spread from approximately one cent in 2020 to 129 cents between January 11 and February 1, 2021. In other words, trading activity exploded while the absolute spread widened dramatically.
The comparison requires an important qualification: the volume and spread figures cover slightly different periods, and dollar-denominated spreads are affected by changes in share prices. These observations do not establish that higher trading volume caused the spread to widen. They do, however, demonstrate why volume alone is an inadequate measure of market liquidity.
Tokenized equities show the same gap. According to CoinGecko's 2026 RWA Report, spot trading volume for tokenized stocks reached $15.12 billion in the first quarter of 2026, compared with $14.84 billion across the second half of 2025. On a monthly basis, that is an average of about $5.04 billion, up from about $2.47 billion, or growth of approximately 104%.
Yet as of March 31, 2026, the total market capitalization of tokenized stocks was approximately $486.69 million. These figures measure different dimensions of the market: transaction activity over time versus outstanding assets at a point in time. A token can be bought and sold repeatedly without requiring its issuer to acquire additional underlying shares for every secondary-market transaction.
Can tokenization improve liquidity?
Under certain conditions, there is evidence that it can. A study in the European Central Bank's April 2026 Macroprudential Bulletin compared tokenized bonds, mostly European corporate issues, with matched conventional bonds from the same issuers. The study found that tokenized bonds exhibited average bid-ask spreads approximately 27% lower than their conventional counterparts, a statistically significant difference. That's not a small gap.
This suggests that tokenization can be associated with improvements in market liquidity, rather than merely an increase in trading activity. However, the finding is based on a small sample in a particular segment of the bond market, and the authors found the opposite result for the few tokenized bonds accessible to retail investors. It should not be extrapolated directly to U.S. equities or treated as evidence that tokenization universally lowers trading costs.
Taken together, these examples show that token trading volume alone is not sufficient evidence when assessing whether tokenized equities create liquidity for traditional markets. The relevant questions are:
Has the underlying stock attracted incremental capital?
Have bid-ask spreads narrowed?
Has market depth increased?
Has price impact declined for transactions of comparable size?
These are the measures that determine whether market quality has genuinely improved.
A new trade is not necessarily a new investment. And a new trading venue is not necessarily a new source of liquidity.
Who Sets the Price of a Tokenized Stock?
If the same company's shares trade on Nasdaq while tokenized exposure trades on Binance, which market determines the price? The question is more complicated than it first appears. Any functioning exchange with buyers and sellers can establish transaction prices.
But price formation is not the same as price discovery. Price formation occurs whenever supply and demand produce an executable market price. Price discovery, by contrast, refers to the process through which new information is incorporated into the efficient price of an asset. A venue can independently form prices without being the primary source of price discovery.
Consider Binance's bStocks. According to Binance's official FAQ, market makers provide quotes for bStocks based on underlying reference prices, inventory positions, and risk parameters. Transactions on Binance's order book are therefore determined by the interaction of market-maker quotes and investor demand.
Binance is not merely displaying a Nasdaq price. Its tokenized securities can trade at prices determined within Binance's own marketplace. However, those prices remain economically linked to the underlying securities through reference pricing, arbitrage opportunities, and applicable conversion mechanisms.
Similar considerations apply to xStocks. These products create additional venues through which investors can obtain equity exposure. They do not automatically create independent sources of fundamental value.
What happens when Wall Street is closed?
The relationship becomes more interesting outside traditional U.S. market hours. When the underlying equity market is closed, market makers may be unable to immediately hedge their token positions through conventional stock trading. Conversion mechanisms may also be subject to operational, timing, or eligibility constraints. As a result, arbitrage becomes less effective, and token prices may temporarily diverge from the last available underlying stock price. This creates a potential opportunity for independent price discovery.
Imagine NVIDIA releases material information after the U.S. market closes on Friday. Its tokenized securities continue trading throughout the weekend. If token prices incorporate that information before U.S. equity markets reopen, the subsequent opening price of NVIDIA shares may move toward the level already reflected in the token market. In principle, tokenized markets could become an additional source of information about future equity prices. But there is an important distinction.
A price that moves first is not necessarily a price that discovers information independently.
The token may simply be responding to information already reflected in derivatives, overseas markets, after-hours quotations, or broader market sentiment. To establish an independent price-discovery contribution, researchers must demonstrate that token prices contain predictive information beyond these existing sources.
What does the empirical evidence show?
Recent academic research offers an early answer. In 2026, Kaitao Lin examined 61 token-underlying equity pairs in One Instrument, Two Technologies: Price Discovery Between Tokenized and Traditional Equity Markets. The study found that more than 80% of the pairs exhibited long-run cointegration. This suggests that token and underlying equity prices generally maintain a stable long-run relationship.
More importantly, the study found that deviations from this relationship were predominantly corrected through adjustments in token prices rather than underlying equity prices. Its price-discovery analysis also indicated that traditional equity markets contributed the majority of information to the common efficient price.
A separate study by Dombrowski and Arshadi examined 57 xStocks and 1,959 events occurring outside traditional exchange trading hours. The researchers found that token returns had very limited explanatory power for subsequent underlying equity returns, with reported regression R² values no greater than 0.005.
In other words, continuous trading infrastructure already exists, but continuous trading has not yet translated into consistently strong, independent price discovery.
These findings suggest that today's tokenized equity markets generally adjust to prices discovered in traditional equity markets, rather than consistently leading them. That does not mean tokenized markets have no role in price discovery, nor does it rule out a greater role in the future.
Price discovery is not a permanent privilege assigned to a particular exchange. It emerges where informed trading occurs, where liquidity is sufficiently deep, and where market participants can respond efficiently to new information.
For now, traditional equity markets remain the dominant pricing anchor. Whether that balance shifts as tokenized markets mature remains an open question.
Does Tokenization Bring New Capital Into Equity Markets?
Even if crypto markets do not currently dominate price discovery, they may still contribute something economically important to U.S. equities. The critical variable is incremental capital. Consider two scenarios.
Scenario A: Existing capital moves to a new venue
An investor already owns NVIDIA through a traditional brokerage account. The investor sells those shares and uses the proceeds to purchase an equivalent amount of tokenized NVIDIA exposure on a crypto platform. The token market records additional trading activity.
But from the perspective of the broader equity market, the transaction does not necessarily represent new capital. The investor has changed the channel through which equity exposure is held. This is closer to distribution-channel substitution than the creation of incremental equity demand.
Scenario B: Crypto capital enters the equity market for the first time
Now consider an investor who primarily holds USDT and has never purchased U.S. equities. Cross-border account-opening requirements, funding procedures, or the investor's preferred trading environment may have limited access to traditional brokerage markets. Through an appropriately structured and legally available tokenized securities product, the investor allocates $10,000 in stablecoins to U.S. equity exposure.
If that subscription leads the issuer to purchase an additional $10,000 of underlying shares through a broker, a transmission of capital from the crypto ecosystem into the traditional equity market has occurred. That is fundamentally different from secondary-market token turnover. And it is arguably one of tokenization's most economically meaningful potential benefits. The important distinction is between new trading activity and new demand for the underlying asset.
Even here, a one-to-one asset-backed structure does not necessarily mean that every subscription creates an immediate, equivalent purchase on a stock exchange. Issuers may use existing inventory, rebalance positions, or execute underlying purchases at different times. The relevant evidence is therefore not simply token issuance, but the relationship between net token subscriptions and actual purchases of underlying securities.
The size of the underlying market matters
The impact of incremental capital also depends on the liquidity of the stock receiving it. Consider two hypothetical companies. The first trades $20 billion per day. Tokenized-equity demand generates $2 million in additional net buying. That represents only 0.01% of the stock's average daily trading value.
Now consider a second stock that trades $20 million per day. The same $2 million in incremental buying represents 10% of its average daily trading value. The potential market impact is entirely different.
For highly liquid securities such as Apple, Microsoft, or NVIDIA, modest additional demand from tokenized products may have little measurable impact on overall market quality. For less liquid securities, broader distribution and access to new investors could be more consequential.
Of course, larger flows relative to existing trading volume may also produce greater short-term price impact, particularly when market depth is limited. Incremental capital does not automatically translate into better liquidity. The long-term outcome depends on whether those investors add sustainable two-sided trading activity, whether market makers can manage inventory effectively, and whether execution costs ultimately decline.
So, Does Tokenization Create New Liquidity?
Return to the two questions that motivated this discussion.
Does tokenization create new liquidity for traditional financial markets?
Or does it simply recreate existing securities within another trading system, with different trading hours, market participants, and order books?
The answer is that both outcomes are possible. If tokenization merely shifts existing investors and their transactions into separate order books, it may primarily create new trading venues rather than new liquidity. If, however, tokenization attracts capital that previously had limited access to traditional securities markets, and efficiently connects that capital to underlying assets through issuance, conversion, and execution mechanisms, it can create genuine incremental demand.
Whether that demand ultimately improves bid-ask spreads, increases market depth, or reduces price impact remains an empirical question. Current research also suggests that traditional equity markets continue to account for most price discovery, even as tokenized markets expand.
Tokenized equities have created new mechanisms for trading existing assets. They have not yet demonstrated that they can consistently replace the pricing role of established equity markets.
More trading is easy to measure. More liquidity is considerably harder to prove.
The next phase of tokenization should not be judged simply by how much volume moves onchain. It should be judged by how much genuinely new capital reaches the underlying market, and whether the resulting market is more efficient, more accessible, and less costly to trade.
That is the difference between building another Wall Street and expanding the reach of the one that already exists.
FAQ: Does Tokenization Improve Liquidity?
What is the tokenization liquidity paradox?
It is the gap between trading activity and liquidity. Tokenized assets can generate large trading volume without improving liquidity. In our hypothetical example, $10 million of tokens that change hands ten times in a day produce $100 million in volume, while the underlying equity market may have seen only the original $10 million purchase.
Is trading volume the same as liquidity?
No. Trading volume is the amount of trading activity over a period. Liquidity is how quickly and efficiently a trade of a given size can be executed, with limited costs, slippage and price impact. In early 2021, GameStop's average daily volume rose from about 6.7 million to roughly 100 million shares, while its average bid-ask spread widened.
Do tokenized bonds have lower bid-ask spreads?
In one study, yes. Research in the ECB's April 2026 Macroprudential Bulletin found tokenized bonds, mostly European corporate issues, had average bid-ask spreads about 27% lower than matched conventional bonds from the same issuers. The sample was small, the few retail-accessible tokenized bonds showed the opposite result, and the finding should not be extrapolated to U.S. equities.
Do tokenized stocks lead price discovery?
Not yet, according to current research. Kaitao Lin's 2026 study of 61 token-underlying equity pairs found more than 80% were cointegrated and that traditional equity markets contributed the majority of price discovery. Dombrowski and Arshadi found off-hours token returns explained very little of later equity returns, with R² values no greater than 0.005.
What is the SEC Innovation Exemption for tokenized stocks?
It is a temporary exemption the U.S. Securities and Exchange Commission introduced on September 17, 2026 for trading certain tokenized stocks (Release No. 34-106402). One of its conditions gives issuers notice and the right to object before a venue lists a third-party tokenized version of their shares. Nine U.S. public companies used that right.
Research References
U.S. Securities and Exchange Commission, Order Granting Temporary Conditional Exemptive Relief for Tokenized NMS Stocks ("Innovation Exemption"), Release No. 34-106402 (2026).
U.S. Securities and Exchange Commission, Staff Report on Equity and Options Market Structure Conditions in Early 2021 (2021).
Hasso et al., Who Participated in the GameStop Frenzy? Evidence from Brokerage Accounts, Finance Research Letters (2022).
CoinGecko, RWA Report 2026 (2026).
European Central Bank, Tokenised Bonds: Assessing Efficiency and Liquidity in a Nascent Market, Macroprudential Bulletin No. 33 (2026).
Kaitao Lin, One Instrument, Two Technologies: Price Discovery Between Tokenized and Traditional Equity Markets (2026).
Dombrowski & Arshadi, Tokenized Stock Markets: Tracking Quality, Arbitrage Limits, and Price Discovery (2026).
This article is for informational and research purposes only and does not constitute investment advice. Hypothetical examples are illustrative and do not represent actual market transactions. Empirical findings are subject to the methodologies and limitations of their respective studies.