Announcing our partnership with Stork Network to bring long-tail Real World Asset feeds onchain.
We’re thrilled to announce our partnership today with Stork to bring bespoke, long-tail real world asset feeds onchain. Brent oil, the Hang Seng Index, copper, and yes, even lean hogs — will all be available to trade on our testnet Beta this month.
Fundamental to our vision is the belief that Real World Assets need purpose-built infrastructure. Copy-pasting RWAs into a model built for crypto, without accounting for their unique features – out-of-market hours, futures contract rolls, price gaps at market open – is not a scalable solution.
As a perps protocol, the existence, reliability, and suitability of a price feed for a given asset is paramount. We found not only that feeds for most long-tail assets we wanted to list didn’t yet exist, but that more accessible feeds (e.g. EUR/USD) had no full-stack solution.
These feeds require protocols to layer on protections against things like out-of-market hours that carry substantial trust assumptions. Protocols listing FX or metals typically rely either exclusively on front-end blocks (!) or a single external market hours API to restrict trading. Even the safest and most reliable FX oracle during market hours isn't safe to use "out of the box" with no additional protocol-side trading restrictions 25% of the week (on weekends when markets close).
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Beyond baseline requirements like sub-second latency and near-perfect uptime, any oracle partner would need to support:
- Market hour integration into price metadata
- Custom price aggregation logic as a function of asset type
- Bid/ask data to approximate underlying liquidity conditions
The latter two are particularly important for longer-tail markets with greater variability in liquidity conditions and underlying price data quality, as well as commodity futures markets with differential contract roll timing.
For instance, medianizing across an even number of number of data providers tracking different contracts risks producing something unreliable like this:
Differences in reported prices will often blow out right around market reopen due to volatility. Not including bids and asks risks making these differences exploitable at scale (far left in the graph is a stale price during market close):
We needed both the flexibility to customize logic according to the unique risks we foresaw for assets no one had brought onchain before, and the expertise of a team with a proven track record in price feed provisioning and dedicated, high-speed infrastructure.
Stork's reputation as a low-latency, SLA-guaranteed oracle provider and more modular, flexible approach made them the ideal design partner to work closely with us on pioneering these bespoke feeds. At launch, the Stork network will operate nodes containing our custom logic and data sourcing, aggregated through a modified version of Stork’s aggregator built to support our unique metadata.
We’re already live in testing and will open our Beta to the public at the conclusion of this testing phase. Our most recent research piece on Chinese real estate covered one of the assets we’re most excited to list for the first time onchain.
We can’t wait to share what we’ve been cooking together and to get this product into the hands of our users!
