Buy a tokenized stock and the price on screen doesn't match the real share's last close — most people's first reaction is that something's wrong. Most of the time it isn't. What you're looking at is a premium or a discount, and understanding how this mechanism works, and where it tends to break down, matters more before you order than obsessing over the trading fee. This isn't a piece about how to buy or sell. It's about one thing: why the price drifts, and how to read it when it does.
The mechanism first: while markets are open, arbitrage pulls the price back
A tokenized stock is designed to track the underlying share 1:1 — the issuer holds the real shares with a regulated custodian, and what trades on-chain or on an exchange is, in theory, just another representation of that same holding. If it's pegged 1:1, the price should track the real share, and shouldn't drift far from it for long.
What keeps that peg tight is arbitrage. During normal US trading hours, market makers and arbitrageurs can see both the real-time share price and the token quote at the same time. If the token trades noticeably above the share (a premium), there's money to be made: sell the token, buy or hedge the share, until the gap narrows to nothing worth trading on. If the token trades noticeably below the share (a discount), the reverse trade pulls the gap back the same way. None of this needs a human to step in and correct it — it's simply a side effect of people chasing profit. As long as arbitrage can actually operate, the token price can't stray far from the real share for very long.
Once US markets close, arbitrage stops too — that's the real source of the drift
The problem is that arbitrage can't run around the clock. Regular US trading hours are Monday through Friday, 9:30–16:00 ET, with holidays closed on top; tokenized-stock trading on-chain keeps going 24/7. Once the real market closes, arbitrageurs no longer have a live price to check against — no anchor means there's no way to arbitrage the gap shut.
At that point, market makers are left quoting on their own judgment: the last close, related futures moves, their own inventory, and a best guess at a fair price. That guessed price and the price the real share actually opens at the next session rarely line up perfectly, and that's the most common source of drift.
Beyond the missing anchor, order-book depth is the other variable that matters. Popular, large-cap tickers have crowded, active token pairs, so any gap tends to get closed fast; illiquid, small-cap tickers have thin books to begin with, and even a moderately sized buy or sell order can visibly move the quote. Stack panic on top of that — sudden bad news causing a rush of holders trying to exit at once, pushing supply and demand further out of balance — and reportedly, discounts during panic windows can exceed 5%. That's not a common scenario, but it tends to happen exactly when liquidity is thinnest and information is most one-sided.
Where the reference price actually comes from: the oracle the issuer plugs in
To give the token price something more objective to anchor against, rather than leaving it entirely to a market maker's gut call, issuers typically wire in an oracle feed as a reference point. Reportedly, tokenized-stock projects built mainly on Solana — the kind issued by Backed and traded on platforms like Kraken and Bybit under the xStocks label — lean heavily on price data from Pyth Network, while projects deployed on EVM chains more often combine Chainlink and other sources for cross-checking, reducing the risk of a single data source being wrong or manipulated.
It's worth being precise here: what the oracle feeds in is a "reference price," not an "execution price." The price actually traded on-chain or on an exchange is still whatever buyers and sellers agree to on the order book. Oracle data is used more in risk controls and liquidation logic — giving market makers a sane anchor for quoting, which shrinks the room for extreme drift, but doesn't eliminate the drift itself. That's why premium and discount still show up during closed-market hours or in thin order books, even with an oracle backstop in place.
Three things to do yourself before you order
Check the gap against the real share's last close
Pull up the real share's most recent trading-day close and subtract it from the token quote you're seeing right now. A quick illustrative example: say the last close was $100, and the token is currently quoted at $104 — the gap works out to (104-100)/100 = 4% (illustrative math only, the numbers aren't tied to any real ticker). Having that percentage in your head tells you whether you're currently overpaying or getting a deal.
Look at order-book depth, not just the top of book
The best bid and ask are just the surface. What actually determines whether you get filled near the price you want is how thick the levels below that are. In a thin book, a moderately large order can push the price several percent in a single trade — you think you're trading at the quoted price, but what you actually get is the price after slippage.
Be careful with large orders during closed-market hours
On weekends and US holidays, on-chain trading keeps running, but there's no live share price to check against, and the book is usually thinner too — the mechanics and risk behind this are covered in more depth in the piece on weekend trading and gap risk. If you're not in a rush to cash out or build a position, waiting until US markets open, arbitrage resumes, and the book thickens back up usually beats forcing a trade into a quiet window.
The drift isn't a bug — it's a built-in feature of this mechanism
It's easy to read this and conclude that premium and discount are a system malfunction, or a sign something broke. The opposite is actually true — as long as markets close and liquidity stays uneven across tickers, the drift will keep showing up. It's an inherent feature of a 24/7 matching mechanism, not an occasional bug.
Flip the angle and the gap was never one-directional to begin with. When you buy at a discount, the money you save is money the other side gave up because they needed to cash out fast; when you sell at a premium, the extra you make is a premium the buyer paid to get filled right now. Who overpays and who comes out ahead depends on which side you're on and when you trade — nobody is inherently on the losing or winning end. Don't read the occasional gap as some guaranteed "buy the dip" or "sell the top" signal — first ask whether you just happen to be trading at the exact moment liquidity is thinnest, before deciding to act.
At bottom, extreme de-pegging usually isn't a failure of the matching mechanism itself — it's a sign of trouble with the issuer's or custodian's solvency, and that's a different risk from the day-to-day price gap covered here, worth understanding on its own; what a tokenized stock actually is goes into more of that background. At the day-to-day level, treating premium and discount as a signal you can read, rather than a jarring surprise, will make your ordering decisions a lot calmer. When you're ready to actually sell and cash out, the process and fees are covered in a separate piece.
Questions you're probably about to ask
Is the platform ripping me off if the token price is above or below the real share?
No — that's premium or discount. While US markets are open, arbitrage pulls the gap between token and share back toward zero. When markets are closed or liquidity is thin, the gap can be noticeable. It's a built-in feature of how the matching mechanism works, not the platform pushing the price up or down on purpose.
How big a premium or discount counts as normal?
There's no fixed normal range — it depends on how popular the ticker is, whether US markets are open, and how deep the order book is. Popular tickers during market hours usually show a small gap; illiquid tickers, closed-market hours, or sharp moves can widen it a lot. Reportedly, discounts during panic conditions can exceed 5%, though most of the time it doesn't get that large.
How is the token's reference price actually set?
Issuers typically plug in an oracle feed as a reference anchor. Reportedly, Solana-based tokenized-stock projects mainly rely on Pyth Network price data, while EVM-side deployments more often combine Chainlink and other sources for cross-checking. This price is a reference anchor — the actual on-chain execution price is still set by buyers and sellers matching on the order book.
How do I quickly tell whether the gap is large before I place an order?
Compare the current quote against the real share's last trading-day close and work out the percentage gap, then check how deep the order book is. If US markets happen to be closed, or the ticker is illiquid, the gap is usually more pronounced — if you're not in a hurry, waiting for deeper liquidity before ordering usually helps.
Read next: Can you trade tokenized stocks on weekends? · What is a tokenized stock (the concept) · How to sell tokenized stocks and cash out