Pyth, supported by market makers such as Alameda Research, Jump Trading, and GTS, said it wants to introduce real-world financial data to a decentralized world, and it has to take a different path from Chainlink’s “use of group wisdom to obtain data.”
Written by: Li Ke
GTS , one of the largest market-making companies on the New York Stock Exchange, recently announced that it will cooperate with the decentralized oracle project Pyth Network to enter the field of decentralized finance (DeFi). Ari Rubenstein, GTS co-founder and CEO, said in a statement: “Real-time market data across asset classes will drive decentralized financial applications a huge step forward.”
Financial market data has always been the lifeblood of traders. At the same time, financial market data has always been a controversial topic on Wall Street. In the past, trading companies have criticized large exchanges such as the NYSE and Nasdaq for unfairly increasing the cost of using financial market data. Now, market makers such as GTS are considering using Pyth to transfer real-world financial data. Lead to decentralized governance.
In addition, it should be pointed out that Pyth Network is an Oracle project on the Solana public chain, dedicated to aggregating off-chain financial data onto the blockchain. In combination with the recent development team behind Solana, Solana Labs has just completed a US$314 million financing. Well-known venture capital institutions a16z and Polychain Capital led the investment, and Alameda Research and Jump Trading, who have a market maker background, also participated in this round of investment. Alameda Research and Jump Trading are both the main investors and supporters of Pyth Network, which makes Pyth Network, an oracle project that has attracted the favor of Wall Street market makers, deserves special attention.
What will Pyth do?
According to the information provided by the Pyth Network website, the project aims to introduce Hifi financial data (Hifi) into DeFi and build a next-generation oracle solution to solve the problem of DeFi’s access to real-world data and deliver real-time real-world finance to DeFi. Market data to build infrastructure for DeFi to support the substantial growth of the market.
Some goals are also listed on Pyth’s website:
Using Pyth data will make smart contract data more accurate
Give DeFi full access to massive high-fidelity financial service data and make smart contracts work smarter.
Connect market data from the world’s largest professional traders and exchanges to any smart contract.
Obtain verified data from high-quality nodes with millisecond speed.
Decrypt Pyth team members
The vision looks quite ambitious, but how can these goals be achieved?
At this stage, the Pyth team has not disclosed the information of the project team members, and has maintained a sense of mystery. The official website only briefly introduced, “The project is composed of professionals in the fields of traditional finance and DeFi.”
Fortunately, Pyth’s GitHub provides some clues. We can roughly understand the composition of the Pyth team members through the code contribution status on GitHub. Interestingly, members of the Jump Trading team appear to be the most important contributors to Pyth. The following are the active participants of the Pyth project we sorted out through information from various parties:
- Jeff Schroeder: Jump Trading Technical Lead (Technical Lead), Linux top geek, mainly responsible for the core code of Pyth;
- Samir Islam: Jump Trading Technical Lead (Technical Lead), high-frequency trading system development, Master of Computer at Oxford University, participated in a lot of Pyth code work;
- Evan Gray: Vice President of Engineering at Jump Trading, involved in a lot of Pyth code work;
- Alex Davies: Head of Production Engineering, Jump Trading, one of the early 10 employees of Jump Trading’s European branch, also participated in the Pyth code;
- Pierre Laffitte: Jump Trading quantitative trader, low-latency statistical trading strategy research and development;
- Richard Brooks: Jump Trading Equity Trader;
- Ed_Crypt: One of the Pyth community leaders, Serum project supporter, Solana ecological supporter;
- Marc Tillement: One of the Pyth community leaders;
Jump Trading is a world-leading high-frequency trading company headquartered in Chicago, and is the settlement unit of CME (Chicago Mercantile Exchange). This company was founded in 1999 by outstanding CME floor traders Bill DiSomma and Paul Gurinas. It employs many PhDs from top universities to study trading strategies.
As of press time, the Jump Trading team has not officially confirmed the specific relationship between the above members and the Pyth project, but the code contribution record on GitHub itself will not lie.
The investment team behind Pyth
At present, Pyth’s main investment institutions are Alameda Research and Jump Capital.
Alameda Research was founded in 2017 by Wall Street trader Sam Bankman-Fried, dedicated to digital currency investment. Alameda Research has incubated the famous digital currency derivatives exchange FTX.
Jump Capital is a US venture capital institution. Its investment fields mainly include enterprise-level technical services, IT healthcare services, marketing and financial services. The digital currency companies invested by Jump Capital include 0x, Curv, Blockfi, BitGo, TradingView, etc., its parent company For Jump Trading.
Why do you want to do Pyth?
Pyth once published a blog post specifically about his expectations for the future business:
Pyth believes that DeFi still has a lot of room for growth. If DeFi realizes its full potential, it may grow to a total lock-up value (TVL) of trillions of dollars. Defi will cover all kinds of institutions from today’s early users. To realize this potential, more ecological projects are needed to assist. For example, the iPhone has opened up a whole new industry, but many supporting ecosystems have been built over a long period of time, making the iPhone so powerful. “The current DeFi is like the iPhone that has just been released.” Pyth Network hopes to become a project to promote the development of Defi.
The latency and data interruption problems of the oracle need to be resolved. DeFi lacks a reliable institutional market data oracle, and Pyth hopes to fill this gap. This type of data has many characteristics and requires a special type of oracle solution. Existing solutions focus on using the wisdom of the group to obtain data, and Pyth Network hopes to complement each other from different perspectives. Because Pyth Network obtains first-hand data directly from financial institutions in real time, it can provide accurate settlement prices in milliseconds to prevent price fluctuations.
Pyth bidders have a lot of data. Over the years, data has become a big business, usually provided by one or several centralized data providers. Pyth Network has attracted some of the largest traders and exchanges with large amounts of financial data. Using the power of decentralization, Pyth hopes to aggregate these unused data to create a high-quality composite market data source.
Pyth believes in a fair and transparent market governed by users. The uniqueness of blockchain is that they provide users with a mechanism to make decisions in a fair and transparent manner. The Pyth network is designed to be open and accessible. From providing and using data to protecting data or helping to determine what data to obtain, all interested and motivated participants will play different roles. By creating a diverse ecosystem of participants, Pyth Network will continue to innovate and strive to provide the market with the tools it needs.
What is the difference with Chainlink?
Pyth Network believes that existing oracles (such as Chainlink) focus on “using the wisdom of the group to obtain data.” Sometimes they just crawl some raw data like a web crawler, while Pyth Network hopes to develop from a perspective that it does not.
Specifically, Pyth hopes to use the high-speed and low-cost characteristics of Solana’s public chain to provide millisecond-level high-fidelity real-time financial data for blockchain and Defi projects, such as stocks, bonds, futures, foreign exchange, and commodity data. These data are often in the hands of a few large centralized institutions, such as large NYSE market-making companies like GTS. Pyth will focus on processing financial data in the real world and put them on the chain, which is also an area where the Pyth team excels.
Preliminary Study on Product Form
Up to now, Pyth has not published white papers or specific project documents, only documents for developers briefly introduce its products:
Account classification: The Pyth blockchain price oracle machine manages multiple accounts on the chain. Its blockchain accounts are divided into three types: mapping accounts, product accounts, and price accounts. Mapping accounts can be linked to each other.
Pyth Network’s blockchain account structure
Among them, each mapping account contains a product account.
Each product account corresponds to an asset (such as BTC/USD or AAPL/USD), and the product account contains “code”, “asset type”, “country/region”, etc.
Each product account contains some price accounts. Price accounts include “product prices” and other indicators. Each price account involves different “price types”, currently including “price”, “average price”, and “volatility”.
Each product may have a slightly different set of attributes, depending on their type, but they all have the attributes of “symbol”, “asset type”, “quote currency”, and “period”. For example, U.S. stock products include various additional reference symbols that can be used to map Pyth products to other industry standard identifiers.
Each price contains a “price” and “configuration” value. “Conf” represents the confidence interval of the price, which roughly corresponds to the bid-ask spread. All “prices” are stored as 64-bit integers with fixed and implicit decimal places defined by the “exponent” field. Therefore, the AAPL price of 12276250 above represents a value of 122.76250 because the “Index” is set to -5 or 5 decimal places.
Each price has a “status”, including: “transaction”, “suspended”, “auction” or “unknown”. Only the “transaction” price is valid. Stock products also include a “corp_act” status, which is used to notify users of any ongoing company events that may affect the price of the product. The “valid_slot” and “publish_slot” fields correspond to the solana slot when the total price is aggregated.
Price summary procedure. Pyth prices represent a summary of “quotes” from multiple markets. The process of deriving the total price is divided into two stages: First, individual bidders submit their price and the value of the solana slot that they believe has been recently confirmed. The second stage collects the latest price from each bidder, discards those prices that are out of date or not in a valid transaction state, and obtains the total price through a simple median.
The Pyth program summarizes the price according to the current slot in the Solana node, which is the “valid_slot” above. Once the slot changes, the Pyth program calculates and publishes the total price based on the new “publish_slot”, and starts to repeat the process with the new “valid_slot”.
The “status” of the aggregate price depends on whether there are valid contributors (such as the “unknown” status) or whether the contributor is in the “stop” or “auction” status.
In the second development version, in addition to mapping accounts, product accounts, and price accounts, Pyth also added Program accounts and made some updates, and plans to migrate from version 1 to version 2. More technical details You can refer to the official website .
Project Progress
Pyth plans its development into 3 stages:
The first stage (in progress). Cover its data to U.S. stock information, digital currency prices, algorithmic trading market information, and market status information; cooperate with companies that have unique data and want to go on the chain; transmit some raw data to the Solana public chain and distribute to the Ethereum Layer1 and Layer2; cooperate with some Dapps of Layer1 and Layer2; improve the official website of the project and build communities such as Discord, Telegram, and Twitter.
The second stage (planned). Increase data coverage to the futures and foreign exchange markets, expand algorithmic trading and add volatility and other data indicators; increase data providers; increase data integration; increase Layer1 support; start a complete website; start pledge, reward and management functions.
The third stage (planned). Increase the coverage of data sets to international stocks and futures; increase data providers; further increase data integration; increase Layer 1 support; introduce fees and penalties and reduction mechanisms.
Obviously, Pyth is still in a very early stage of development, and a Beta version will be launched next. The Pyth team also stated on the official blog that it hopes to cooperate with blockchain project parties that will use financial data, and also hope to cooperate with institutions with low-latency financial data to cover a wider range of real-world financial data.
