#11 Pyth in Chicago
This edition will cover the very first Pyth Workshop we hosted alongside the Solana Chicago Hacker House, as well as provide an in depth review of the Pyth network Whitepaper.
The Pyth network is a vision coming to life: one that imagines the world of decentralized finance (DeFi) gaining comprehensive access to high-fidelity (HiFi) financial markets data securely and reliably.
In other words, the Pyth network is a specialized oracle network that focuses on sourcing continuous real-world and crypto-related market data originating off-chain and streaming it on-chain at sub-second speeds for smart contract consumption regardless of their blockchains.
This is an ambitious goal because financial market data is sufficiently unique: there are very few available sources, and those sources have very tightly controlled distributions. In addition, the oracle network needs to be able to combine such latency-sensitive data in way that optimizes not only accuracy but which increases security as well given how dependent many blockchain applications are on the accuracy of this type of data.
On the back of the momentous release of the Pyth network whitepaper (with bigtime coverage from the Financial Times) on Tuesday, 18th January 2022, we wanted to provide the Pythian community a useful succinct summary of its contents. We encourage you to reach out with questions and feedback in our Discord or Telegram.
Growth in DeFi requires high-fidelity, time-sensitive, real-world data, direct from the source, and made available to users across all layer one blockchains. However, at present, financial market data is often accessible to only a limited set of institutions and users, as incumbent players maintain strict control over both live and historical price feeds. The paradigm is shifting.
The Pyth network is a next-generation oracle solution that aims to bring this valuable financial market data to the general public at large. The network does so by incentivizing market participants — trading firms, market makers, and exchanges — to share the price data collected as part of their existing operations. The network aggregates this first-party price data on-chain and makes it available for use by either on- or off-chain applications. End-users of Pyth data can elect to pay data fees to protect against potential oracle failures. Delegators choose which product (price feed) and a specific publisher to back to earn data fees in exchange (or lose their stake if the oracle is inaccurate due to publishers’ faults). The incentivization system operates through (PYTH) token staking by network participants and fees voluntarily paid to data publishers. The goal of the design is to make the Pyth network self-sustaining and decentralized.
3 different types of stakeholders will interact within the network:
Publishers publish price feeds and earn a share of data fees in exchange. Publishers are typically market participants with access to accurate, timely price information. The protocol rewards publishers in proportion to the quantity of new pricing information that they share.
Consumers read price feeds, incorporate data into smart contracts or dApps, and optionally pay data fees. Consumers can either be on-chain protocols or off-chain applications.
Delegators stake tokens on a specific product and publisher to earn a share of the data fees in exchange for potentially losing their stake if the oracle is inaccurate.
Any actor may have multiple roles within the network. For instance, data publishers (or consumers) may additionally decide to delegate tokens to earn additional data fees.
Network participants will interact following 4 on-chain core mechanisms:
Price aggregation combines the reported prices and confidence intervals of individual publishers into a single price feed and confidence interval feed for a specific product (e.g. BTC/USD feed). This mechanism is designed to produce robust price feeds — feeds whose prices cannot be significantly influenced by small groups of publishers.
Data staking allows delegators to stake tokens to earn data fees. The delegators in aggregate also determine the level of influence (stake-weight) that each publisher has on the aggregate price. In addition, this mechanism determines whether delegators’ stakes are slashed. Finally, the mechanism collects data fees from consumers and distributes a share to delegators (initially set at 80%). The remainder (20%) goes into a reward pool that is distributed among publishers.
Reward distribution determines the share of the reward pool earned by each publisher. Each product has a reward pool that delegators can stake into. The reward distribution mechanism preferentially rewards publishers with higher quality price feeds and reduces the likelihood that uninformed publishers will earn rewards.
Governance will be using a coin-voting system that will help determine the high-level parameters of the three mechanisms above. Parameters include what types of tokens may be used for data fees; which products are listed on Pyth; the share of data fees allocated to publishers, delegators, and other uses; the number of PYTH tokens that publishers must stake or enable claims to be filed against a product, and more.
Overall, every participant will have incentives to fully engage with the network:
Publishers are incentivized to stake PYTH tokens to participate in the protocol and earn a share of the rewards. Publishers earn a share of the data fees for the products they price. The data fees for a product will likely grow in proportion to consumer usage of the price feed. Publishing erroneous (voluntarily or not) data to the network may lead to the publisher's stake being slashed.
Consumers are incentivized to pay data fees for two reasons. First, data fees enable applications to reduce the risk of using Pyth price feeds as they would receive a payout in case of failure. Second, paying data fees attracts more publishers to the product, which improves the robustness of the price feed.
Delegators are incentivized to participate in the protocol to earn data fees (coming from consumers’ data fees). Delegators will initially earn attractive payments, but competition between them will reduce the payments over time as the market becomes more efficient.
Pyth Workshop & Chicago Hacker House
From the 17th to the 21st of January, Jump Crypto and Solana Labs co-hosted the inaugural Pyth Workshop alongside the Chicago Hacker House. The community was 150 strong including the data providers, application users, and builders alike. A cold Chicago wind could not stop that Pyth heat.
It was with great pleasure for the Pyth network to host many talks for its stakeholder community as well as for the Hacker House participants. Topics covered were various from the Pyth infrastructure, to Solana RPC with, of course, the long-sought Pyth Whitepaper Walkthrough. Find the whole Pyth Workshop playlist here. If we were to provide a curated list, we would recommend the below ones:
Understanding the Pyth Architecture by Samir Islam & Harnaik Kalirai
Wormhole 101 with Evan Grey
Meanwhile, in the Hacker House, approximately 250 shadowy super coders got together in a purple (Pyth?) lighted room. On the last day, a handful of demos were held with the likes of a multi-sig wallet, tools for automatic NFT actions, Twitter verification with NFT certificates, or basket swaps...
All this ended on a lighter touch, as all fellow participants gathered one last time at Tao to bid its farewell.
Since, the Hacker House has announced its upcoming schedule and it will be packed! Starting Feb 1st until 5th, the LA Hacker House is already full with 350+ signed up. From LA, the Hacker House will then go to Seattle (9-13 February), Singapore with Zeta Markets (15-20 February), Dubai (15-20 February), and many more.
During those past two weeks, we saw a handful of new protocols launching on Solana, all with a different area of focus.
On the 17th of January, Zeta became (to our knowledge) the first DeFi protocol to release dated futures (weekly SOL expiry for now) for everyone to leverage. With a deposit limit initially implemented ($1,000 per account), Zeta has already successfully resolved 2 weekly SOL futures (#1 & #2) and their options for a total of just over $2M. We are very proud to see the Pyth network being leveraged as the settlement reference for this one of kind DeFi product. With the caps raised, we are expecting to see significantly greater volume on these primitives.
On the same day, entered UXD. UXD aims to solve an incredibly difficult problem: creating a stablecoin that is stable (1 UXD = 1 USD), decentralized (no censoring), and capital-efficient (no overcollaterization). How does UXD work? UXD is pegged to the US dollar using derivatives (currently Mango Markets is integrated and soon others). Since it is backed 100% (meaningfully collateralized) by a delta-neutral position, users will always be able to redeem 1 UXD for 1 USD worth of assets. If UXD deviates above or below the USD peg for any reason, traders will be able to make risk-free profits and bring the price of UXD back to the peg. Learn more from their docs.
So even if the Pyth network is not directly embedded into UXD, them leveraging the on-chain perpetuals platform funding rate, they are indirectly relying on the difference between the platform Mango Markets mark price and the Pyth index price.
Finally, on the 27th, a new decentralized perpetual platform went live on Solana mainnet. We are looking forward to 01 Exchange evolution as they are working on one of the most innovative products out there. Based upon the discovery of Dave White, Dan Robinson, Zubin Koticha, Andrew Leone, Alexis Gauba, Aparna Krishnan, 01 aims to release Power Perpetuals.
A power perpetual is a perpetual derivative indexed to a power of the price of some underlying instrument. Powers provide option-like exposure because of the convexity of the payout. When prices move in your favor, you earn a lot more than you would lose if prices move against you.
For reference, 01 did a simulation for SOL with the 2021 price action to demonstrate the gaps between SOL and sqSOL returns.
That is all for our 11th newsletter — Thank you for reading, and don’t forget to subscribe and share!
We can’t wait to hear what you think! Feel free to join the Pyth Discord server, follow Pyth on Twitter (here is our Chinese Twitter), join the Telegram (here is our Chinese Telegram), read our Medium blogs to learn more, and ask any questions you may have.