Pythiad #5: Last straight before 2022
Welcome to the fifth installment of the Pythiad, the Medium Pyth Network newsletter!
For those who missed Pythiad #1, Pythiad #2, Pythiad #3, or Pythiad #4 be sure to check them out. We covered just about the entire history of Pyth network, from our ‘hello world’ moment to our various partners, including our data providers, partner projects utilizing our feeds, and many other topics.
To our followers, we say thank you again for all your support, feedback, and positivity! And to our newcomers, we say welcome.
We are delighted to have you on board. As always, there is much to discuss.
- Pyth Network Developments
- Our Publishers
- Solana Breakpoint Conference
- Pythian Community
- Pyth Metrics
Pyth Network Developments
Since the release of the last Pythiad, a month ago, some updates have made the headlines such as Tower Research Capital joining Pyth’s impressive roster of over 40 first-party data providers, and the Solana Conference. Other developments were more lowkey, though discoverable for the most dedicated Pythians. Everyone’s work the past month represents another critical step towards the next generation of DeFi.
As more and more people come visit pyth.network to track prices as they would do on Yahoo Finance or any other similar website (except it is high-quality streaming data at Pyth), it felt only normal to ship couple updates to improve the user experience.
1. When checking the historical charts (1D, 1W, 1M), loading times have been improved up to 10x
2. You can now supply the cluster (testnet, devnet, mainnet-beta) and range (LIVE, 1D, 1W, 1M) parameters directly in the URL
So come test pyth.network out and let us know the next needed upgrades
During the month of November, the Pyth network has launched 2 new crypto feeds:
Those two assets were significantly requested by the community as the liquid Solana staking solution developed from Marinade has been widely adopted within the Solana ecosystem and UST: a USD pegged stablecoin backed by LUNA and the Terra blockchain, as is on its way to becoming the most widely used decentralized stablecoin on blockchains.
As of today, mSOL gathers $1.4B in value staked and the addition of this asset to Pyth provides DeFi platforms a 1st party and high-quality feed for usage. In practice, it means that you may now use mSOL as collateral in many borrow/lending platforms (Solend, Port, Larix) as well as perpetual protocols (Mango Markets) and synthetics dApps (Synthetify). This mSOL utilization enables users to enjoy all the benefits liquid staking bring (liquid staking and staking pools enable to further decentralize the Solana blockchain as well as generate a yield from staking rewards) while leveraging it as collateral too.
On the other side, TerraUSD (UST) is an algorithmic stablecoin with over $7B in circulation today. UST is now more and more usable outside of the Terra ecosystem: some exchanges offer markets denominated in UST in addition to USDC and USDT and now other blockchains start embracing TerraUSD as successful Solana protocols like Saber or Mercurial offer (stable)swaps with UST. The latter being added within Pyth further empowers Solana dApps to start accepting this decentralized stablecoin as an asset on their platforms — Port Finance being an example.
We deeply understand the ecosystem need and community request to further accelerate the assets being sourced within Pyth but given our initial design — sourcing only first-party data for higher quality, speed of access, and legal considerations — it means that there may be hurdles to immediately listing some of the newer and shinier tokens as price feeds, as reliable sources need to be secured. With this in mind, the whole Pyth network has been actively looking to come up with a solution that we hope shall be soon unveiled to the community. We are very excited about this evolution as it will further empower the whole Solana DeFi ecosystem and open up the horizon to replicate this with the other blockchains through the Wormhole, which will give Pyth access to Ethereum, Terra, BSC, Polygon and many more to come. So stay tuned!
To review all of our available price feeds, have a look at our markets page. We welcome all feedback and requests regarding the next set of instruments and asset classes — the world of data is big, and we are just getting started here at Pyth!
A New Aggregation Formula?
One of the core tenants of Pyth is to rely on high-quality, first-party data as inputs for its aggregated output to make it valuable (great accuracy & robustness). The reason is almost self-explanatory: trash in, trash out. With poor initial sources (and without magic), it is impossible to make the aggregated output of high quality. Meanwhile, with valuable data as inputs, the first hurdle can be jumped over. Still, a second one remains, and it relies on the inputs aggregation into an even more high-quality output.
By now, you are probably aware that Pyth not only provides a live market price for assets but it does also offer a confidence interval alongside it — read more on the Confidence Interval. And this extra data provided — mapping out the uncertainty one publisher has towards the price he provides — actually enables the Pyth network to leverage a smarter aggregation method.
Now let’s dive into the new price aggregation proposal Pyth has made. You may find our full blog post here.
→ We want Pyth’s aggregation algorithm to have 3 properties:
1. Robust to manipulation
If most publishers are submitting a price of $100 and one publisher submits a price of $80, the aggregate price should remain near $100 and not be overly influenced by the single outlying price.
2. Aggregate price should appropriately weight data sources with different levels of accuracy
Pyth allows publishers to submit a confidence interval because they have varying levels of accuracy in observing the price of a product. This property can result in situations where one publisher reports a price of $101 +/- 1, and another reports $110 +/- 10. In these cases, we would like the aggregate price to be closer to $101 than $110.
3. Aggregate confidence interval should reflect the variation between publishers’ prices
In reality, there is no single price for any given product. Every product trades at a slightly different price around the world and so we must be able to reflect these variations.
→ How does the suggested aggregation algorithm achieve the 3 above properties?
The first step of the algorithm computes the aggregate price by giving each publisher three votes — one vote at their price and one vote at each of their price +/- their confidence interval — then taking the median of all the votes.
The second step computes the distance from the aggregate price to the 25th and 75th percentiles of the votes, then selects the larger of the two as the aggregate confidence interval.
Now, let’s put everything together and visualize it with 4 scenarios.
In the following graphs, the red star depicts the aggregate price and the bold red line depicts the aggregate confidence interval. The grey circles represent the 25th and 75th percentiles of the votes — the further one of these from the aggregate price determines the confidence interval’s width.
- Scenario 1
One “confident” publisher (tight CI) is an outlier to the cohort but does not impact the final aggregated price. Its only impact will be a greater aggregated confidence interval that could highlight a price dislocation of the asset on different venues.
- Scenario 2
It demonstrates how publishers with tighter confidence intervals (while having overlapping quotes with the rest of the cohort) can exert greater influence over the location of the aggregate price.
- Scenario 3
It features publishers in overall “agreement” regarding the price and their relative uncertainty towards it. The final result shows that the aggregate confidence interval accounts for each publishers’ CI and gives identical results to the ordinary median.
- Scenario 4
Publishers publish distinct prices with non-overlapping CI. In this case, all votes of a single publisher will be adjacent in the sorted list and will be treated as a single vote.
Even if we would not be in any of the above scenarios mentioned, the aggregate price will always lie within the 25th-75th percentile of the publisher’s prices.
In addition, we’re working on a staking system for publishers that incentivizes them to provide accurate data, and in that system, each publisher will have a varying amount of stake. All of the results also hold for stake weights if we simply replace the % of publishers with the % of stake controlled.
Open Source? Always Has Been
Recently, there was an increased focus on the Solana ecosystem (thanks a lot to Solana itself, the Breakpoint conference & the continuous building by tons of very skilled teams) and, among all the takes, one somehow broke out versus the others: most Solana protocols would be closed sources as showed by The Block article — “A surprising number of Solana projects are closed-source — but now the tide may be turning”.
In our quest to make high-quality first-party data available freely to everyone — which is not the case today in traditional markets or on-chain — it only seemed logical for us to work out in the open alongside the community and so the Pyth repo has, since day 1, been open-source.
This allows anyone to not trust but verify the code — one of the core tenants around here — but it also enables anyone to voluntarily contribute to the protocol and achieve together our long term goal: building a digital marketplace of institutional grade, high fidelity financial data to offer the best data to the world. So we would like to deeply thank everyone that has either logged issues, submitted PRs, provided feedback, or requests.
With this in mind, we have 2 concrete examples of why building out in the open is powerful and we wanted to showcase them:
This initial Python client will very soon get improved thanks to the contribution of maffswiffmatt#5027 and his (also open-source) code: https://github.com/johnstonematt/pythpy.
Months pass by and the Pyth roster of publishers continues to stack prominent financial providers as contributors. This includes the world’s most prominent trading firms, exchanges, and crypto native companies, all together under one roof, helping to democratize market data. Please reach out if you want to join this cohort in helping to shape the next digital marketplace of institutional grade, high-fidelity financial data.
This month new additions to the growing Pythian community will further strengthen our ability to provide 24/7 high-fidelity market data for cryptocurrency, equity, FX, and commodity assets.
- Founded in 1998, Tower Research Capital is a leading quantitative trading and technology company that has built some of the fastest, most sophisticated electronic trading platforms in the world.
- TRC has now offices around the world in New York, Chicago, Charleston, Montreal, London, Amsterdam, Gurgaon, Gift City, Singapore, Hong Kong, and Shanghai
- XBTO is a global institutional market maker and asset manager providing cryptofinance trading and liquidity provision to the world’s most established exchanges.
- Established in 2015, XBTO was the ﬁrst to provide institutional-grade liquidity to major trading platforms.
- Since then, XBTO has become a recognized and leading proprietary algorithmic trader and venture capital firm.
- Founded in 2019, Apifiny is a global digital asset trading network for institutions.
- The company’s vision is to create one, global trading marketplace for digital assets.
- Apifiny HEX is designed to provide the digital asset community with the best of centralized and decentralized trading, including zero taker fees, global price discovery, and predictable liquidity from automated market making (AMM) and global, centralized exchanges.
- CDAP a technology-forward digital asset trading firm. Headquartered in Lisbon, Portugal, but with global reach, CDAP specializes in providing liquidity in listed and OTC cryptocurrency derivatives, as well as spot markets.
- After its founding in 2016, CDAP leveraged its advanced technology to rapidly grow to be one of the top liquidity providers on several leading global exchanges.
To review all our 1st party data providers, you may check the Publishers tab on the website.
Solana Breakpoint Conference
If you would like to catch up with all the amazing panels and speakers, we urge you to go check the Solana Youtube page. All was recorded so you can catch up at your own speed.
More and more keep added to the Solana page so be sure to regularly check it out — a shortlist of worthy panels that happened — of course not comprehensive.
Opening panel: State of the Network (with Anatoly Yakovenko and Raj Gokal)
Closing panel: Closing Ceremony (Raj Gokal & Anatoly Yakovenko)
EVM (Ethereum) dApps on Solana: Neon Labs Cross Chain EVM for Solana Workshop
Brave Software to join Solana: Talk by Brave’s Brendan Eich with Anatoly Yakovenko
Jump Crypto within Solana: Why’s a Quant Trading Firm Building on a Blockchain?
Blockchain Trilemma: Debate: Scaling and the Censorship Resistance Threshold
A Multi-Chain World: Multi Chain Futures: What Builders and Investors Are Watching For
As panels went on, one thing turned out to be very clear: the exponential growth Solana has experienced and maintained throughout the past year. The Pyth network is very excited to be part of this wonderful journey which will get even better once the 1st Pyth data will be bridged with the support of the Wormhole (which now bridges Solana <> Ethereum <> Terra <> BSC <> Polygon with more to come).
Whether you missed the event or have made the trip to Lisbon, Portugal, we can all enjoy this nice video from Solana and cherish those memories!
Alongside the conference, Pyth held 2 events that had a huge turnout. We would like to thank again all the people that came and our wonderful organizing partners: Audius, Burnt Finance, Commonwealth, Figment, HXRO Network, Injective, Lido, Project Serum, and Wormhole!
A Hacker Life
During the Solana Conference, on the side of all the official events & venues, Xico and the Metaplex team organized the Lisbon Hacker House to allow anyone to have a place where they could build in peace or alongside other Solana builders. This Hacker House ended as one of the places to be in Lisbon for everyone partaking in the Solana ecosystem, for those who missed it, here is a short recap video.
This initiative was a great success and proof of a tightknit Solana community — many protocols even issued prizes for building on top of their product or new features. About $250K, all voluntarily contributed by teams, were up for grabs.
Building on this success, a new ephemeral Solana Hacker House will take place early December in Miami, USA. For 1 week, December 1–7, Solana builders will meet up again and this time to take down other challenges.
Having witnessed firsthand the hit the Lisbon Hacker House was, Pyth has decided to become an official sponsor of the Miami Hacker House! Since its inception, Pyth has been open-sourced and so welcomes any developer to participate in the building of the next digital marketplace of institutional-grade and HiFi financial data. To further incentive community building, a Pyth prize will be presented shortly — so stay tuned for details!
Figment: a new Pythian
In the same vein that the Miami Hacker House, Pyth is committed to further pushing the development of the network from various contributors — the more the merrier — and it only seems normal to welcome Figment, whose mission is to support the adoption, growth, and long term success of the Web 3 ecosystem, within the Pyth network.
As contributors and partners, Figment will be working closely with the Pyth network participants to bring more functionality and usability to the Pyth HiFi market data. Figment will also be creating a Pyth network knowledge base on Figment Learn, which will guide developers through their first Pyth network data integration. This will include future incentives for developers who create additional tutorials that expand on Pyth network’s use cases.
“DataHub aims to greatly improve the access to leading Web 3 protocols and we believe oracles will play an essential role in the Web 3 stack. With this partnership, we will help Pyth become a dominant solution within its category by helping developers and publishers leverage its full potential.” Yannick Folla — Product Lead at Figment.
Since the last Pythiad, the Pyth network has decided to increase its reach and make the community feel at home! Thus, we have officially launched our Chinese Twitter account: @PythCHN — so be sure to follow! Stay tuned as more channels look to be launched but please be careful to not fall for scams. We will make announcements on our existing socials whenever a new communication channel is opened.
Below are all the places you can currently follow us, interact or keep updated on all Pyth related things, whether it’s about data providers, protocols, or the general ecosystem:
Here arrives a new section (that will become recurrent) for the Pythiads. Month in, month out, we will share with you some data-driven insights on the Pyth evolution — feel free to suggest any type of data you’d like to see. Below data points are not comprehensive and as we continue, pretty much anything that generates data will be at some point incorporated into this section.
Data Providers Onboarded
In mere 7 months, the Pyth has onboarded 40 data providers to contribute their proprietary market data to the Solana blockchain and the network. Such collection of first-party data publishers under one roof already makes Pyth one of the — if not the #1 — platforms with the highest data quality in the world (both blockchain & legacy wise). The progression was steep until now and we do not plan to slow down any time soon as the more data gets in the network the more accurate & robust the feeds will become. We leave it to the community to make guess on how many partners we will have contributing to the Pyth network by the end of 2022!
As mentioned previously in this Pythiad, providing to dApps the most possible price feeds (without sacrificing quality) is of utmost importance as it enables DeFi protocols to make assets “productive” in some manner for users. Since the initial set of assets sourced, the total number of feeds has doubled. We are content but not satisfied by this progression as there are thousands more assets (from any asset class) that could be worth having within Pyth. We are working towards resolving this so stay tuned as it may come quicker than expected!
Some may argue that if something was not picked up by CT (Crypto Twitter), this may have never happened. Thus, let’s visualize Pyth progression towards clout with the evolution of our monthly new Twitter followers. We are very grateful for all the ones already accompanying us in our common journey to provide high-quality data freely and transparently to everyone and look forward to all the future newcomers as the Pythian world will take over!
Pyth has succeeded, so far, in bringing on board 40 of the world’s most prominent trading firms, exchanges, and crypto native companies to contribute their proprietary data to the network. It is — according to us — unseen both in crypto-land and the tradfi-world that so many prominent financial providers (who are often competing against each other) have gathered under one roof, the latter located on the Solana blockchain. With that in mind, we launched the Pyth LinkedIn to easily reach out to this particular audience which for now has not joined CT.
Another medium of communication we have been using to enable any Pythians to be kept in the loop of Pyth advancements without much work is our Substack. Indeed, now anyone can subscribe to the Pyth bi-weekly newsletter and will receive it directly in its mailbox.
As always, the agenda may shift depending on some unexpected occurrences but — even with some — the Pyth network has in sight some major ongoing developments, improvements, and announcements that should be revealed during December and will be deep-dived for the last Pythiad of 2021.
So, to not miss anything, we urge you to join us on our various socials — listed previously in the blog — and you may even start trying to guess what will be the Pyth news of December!
This is the end of Pythiad #5!
If you want to catch up on the first → Pythiad #1: The Journey so Far
If you want to catch up on the second → Pythiad #2: Liberating First-Party Data
If you want to catch up on the third→ Pythiad #3: Pyth Laboured in September
If you want to catch up on the fourth → Pythiad #4: Ignition at a glance
Future newsletters (the next one will already be the last of the year!) will continue to summarize Pyth’s monthly progress and exciting things happening in our ecosystem. They will be sweet, succinct, and pithy.
Thank you for reading!