Pyth Network has added New York Stock Exchange (NYSE) market data to its distribution service, giving financial trading platforms access to prices from the two major US stock exchange groups.
The Nov. 11 announcement follows Pyth’s September approval to distribute Nasdaq Basic data. Both feeds are available through the company’s Data Marketplace, which supplies financial information to applications using blockchain technology and conventional trading systems.
The NYSE agreement covers five equity exchanges: NYSE, NYSE American, NYSE Arca, NYSE National and NYSE Texas.
At the center of the arrangement is NYSE BQT, a real-time Level 1 feed containing trade prices, closing prices, consolidated volumes and the best available bids and offers. Trading halt notifications, resumptions and short-sale restrictions are included.
Much of that information has practical uses for prediction markets offering event contracts tied to US equities. Consider a contract asking whether a particular stock will finish above $200. The exchange’s official closing price can determine its outcome, provided the contract specifies that benchmark.
Trading interruptions can complicate matters. An unexpected halt, for instance, may leave a contract without the usual stream of market prices.
Pyth already publishes equity indices that track prices outside regular US trading hours. The NYSE feed adds official exchange information, allowing applications to compare extended-hours movements against established closing prices.
Customers won’t receive NYSE BQT simply by subscribing to Pyth. They must arrange the appropriate licensing directly with NYSE, while Pyth handles distribution.
“Market data is now consumed by software more than by screens,” Pyth said in its announcement.
Kalshi and Polymarket among existing Pyth customers
Pyth already counts several prediction markets among its data customers. Kalshi and Polymarket already use its data services, although their arrangements cover different products and requirements.
Kalshi signed up for Pyth Pro in April, selecting the service to supply settlement prices for its Commodities Hub. The contracts cover gold, silver, crude oil, natural gas and agricultural products. Market makers can also obtain prices directly.
Months earlier, in October 2025, Kalshi had agreed to become a publisher on the Pyth network.
Under that arrangement, Kalshi contributes its own event-market probabilities, which Pyth distributes across more than 100 blockchains. Rather than obtaining prices for settlement, Kalshi is supplying its market information for use elsewhere.
Polymarket’s relationship with Pyth Pro covers commodities, major equity exchange-traded funds and individual US stocks.
Prices arrive through WebSocket connections, providing a continuous feed that traders can compare with the benchmarks governing their contracts.
Jupiter Predict is another customer. Its markets involving Bitcoin and SpaceX-related outcomes use Pyth Pro, adding to the company’s presence among blockchain-based prediction platforms.
The customer list spans different regulatory environments and trading models. Kalshi operates as a federally regulated US exchange, while Polymarket has historically served international customers through blockchain-based markets.
There has been no announcement that Kalshi, Polymarket or Jupiter Predict has incorporated the newly available NYSE feed. Their existing use of Pyth nevertheless places the exchange’s data within reach of companies already familiar with its infrastructure.
For Pyth, the Nasdaq and NYSE agreements also extend a business built around cryptocurrency and decentralized finance into traditional equity-market information.
How Pyth’s data delivery works for event contracts
Pyth uses an on-demand system for delivering prices to blockchain applications, rather than continually writing every update to the blockchain.
Traditional push-based oracle services generally publish fresh prices at scheduled intervals or after a sufficiently large market movement. Those updates remain available for smart contracts to reference, whether anyone needs the information immediately or not.
Pyth takes a different route. Price information is maintained off-chain, with cryptographically signed updates retrieved when an application requests them.
A decentralized exchange opening a leveraged position, for example, can obtain a recent price during the transaction. A blockchain-based prediction market can use the same mechanism when its contract requires a verified financial price.
The arrangement reduces unnecessary on-chain updates and the associated transaction fees. Fetching and verifying a price still costs money, but applications aren’t continually paying to publish information they haven’t requested.
It can also provide more current pricing than a feed awaiting its next scheduled update, although actual performance depends on the data source and the application.
There is a trade-off in implementation. Applications must accommodate the retrieval and verification of signed updates during transaction processing, rather than simply reading prices already recorded on-chain.
NYSE data broadens Pyth’s reach beyond blockchain markets
For financial prediction markets, timing can be particularly important. A contract settled against a stock’s closing price needs the appropriate benchmark, not merely the most recent trade available when settlement takes place.
The exchange data itself doesn’t settle that question. Each operator’s contract rules determine the price source, timing and conditions used to establish the result.
Pyth also supplies information through conventional APIs, so customers don’t need blockchain-based settlement systems to use its services.
That distinction matters for the NYSE agreement. Its potential customers aren’t confined to decentralized exchanges or cryptocurrency trading platforms.
Traditional financial applications, including prediction market operators using off-chain infrastructure, can also receive the data under the required licensing arrangements.