What is an Oracle?

To know what Pyth is, we first need to know what an oracle is. The function of an oracle is to obtain external data and apply it to a contract, ensuring the accuracy and timeliness of the data. Since most contract processing relies on information and data outside the blockchain, the underlying blockchain and smart contracts of DeFi are relatively closed systems and can be simply understood as third-party data proxies.

In the world of blockchain, oracles are responsible for finding reliable data sources and providing prices to DeFi smart contracts for execution, while users are the operators of these contracts. From the process, it is easy to see the importance of oracles in providing prices. They must ensure the real-time and reliable nature of the data source for the smart contract to function properly.

What is Pyth?

Pyth Network is currently the largest first-hand financial data oracle network, supporting real-time price-feeding services from over 90 data suppliers including traditional financial institutions, cryptocurrency markets, foreign exchange, and commodities. Pyth supports data from over 40 top-tier institutions in both traditional finance and cryptocurrency markets, such as Bloomberg, Hong Kong Stock Exchange, Nasdaq, Jump Trading, Virtu Financial, GTS, and FTX, one of the major supporters of the Solana blockchain.

As a star project on the Solana blockchain, the team behind Pyth Network has a mysterious background. However, some information has been discovered through the records on GitHub. The GitHub code records show that the largest contributors to Pyth Network are members from Jump Trading, including code submissions, code reviews, and suggestions. Jump Trading is a Chicago-based company specializing in quantitative trading, with deep expertise and experience in financial technology and mathematical modeling. With the involvement of Jump Trading’s professional technical team, it is believed that Pyth Network will be able to develop more stably. This collaboration will help drive the development and innovation of Pyth Network in the field of financial data protocols.

Source: https://pyth.network/blog/what-is-the-pyth-network

Pyth claims to provide High-Fidelity data services, which means the data is highly professional and reliable, and the data sources minimize loss and are close to lossless state.

To achieve High-Fidelity, Pyth first supports over 40 blockchain mainnets, over 230 DAPP data integrations, and over 380 full-chain price feed data. Secondly, Pyth’s data is directly provided by the aforementioned data organizations through oracle nodes, which can directly provide prices and data to smart contracts. Pyth aims to leverage high-quality data sources and a high-performance underlying layer network of public chains to bring real-time external data onto the chain, thereby enhancing the potential of the DeFi market.

Pyth Operating Mechanism

Pyth Core Mechanism: Pull Price Update Model

Pyth Network utilizes a price update model called the Pull Price Update Model, which is different from other oracles and forms the basis of its efficient and accurate data updates. Currently, most oracles use a push model where the oracle runs a process off-chain and continuously sends transactions to update prices on-chain. In contrast, Pyth Network does not have this off-chain to on-chain push process, and instead delegates this task to the users of Pyth Network.

Price updates in Pyth are created on the Pyth Network and transmitted off-chain through the Wormhole network. These updates are signed so that the on-chain Pyth program can verify their authenticity. Anyone can submit a verified update message to the Pyth contract for updating the prices on-chain, as this is a permissionless operation. Typically, users who utilize prices from Pyth Network will submit a transaction that both updates the price and uses that price in downstream applications.

It is important to note that on-chain prices can only progress forward in a timely manner. If a user submits a Wormhole message with a more recent price, the Pyth program will not fail but also will not update the price. This means that when users automatically update prices and interact with Pyth-driven applications, there is no guarantee that the prices read by the applications will be equal to the prices submitted by the users.

Pyth Workflow

Source: @pythnetwork"">https://medium.com/@pythnetwork

1. First, professional and high-quality data sources are crucial. After obtaining the prices from data institutions, Pyth estimates the value range of the data through its own “confidence interval” to ensure data security and reliability. For example, if the current price of ETH is $3,000, Pyth will calculate a price range of approximately ±$30, providing an error range. The smaller the range, the higher the precision, which gives users a good reference.

2. As for the delegators, which price should be considered after receiving data from various institutions? Pyth relies on existing data sources, historical performance, and data accuracy to assess the quality of the data sources and determine which data provider Pyth should use.

3. Curators, like delegators, operate on the Solana network. The main role of curators is to identify and provide the data needed in the market, including urgent data requirements. Additionally, both curators and data providers receive rewards from Pyth.

4. Pyth aggregates prices through its own “confidence interval.” For example, if one data source provides a price of $101±$1, and another publisher reports a price of $110±$10, Pyth aims for a total price closer to $101 rather than $110, and the overall confidence interval should reflect the variation between publisher prices.

Price Aggregation Mechanism
Source: ​​https://docs.pyth.network/documentation/how-pyth-works/price-aggregation

After completing the price aggregation, if further operations are conducted on the Solana network, Wormhole is not required. However, if subsequent operations are not carried out on the Solana chain, Pyth’s Layer1 cross-chain bridge functionality with Wormhole is needed to make Pyth’s oracle data available for all chains to use.

In addition, Pyth uses a reward and punishment mechanism to guide the behavior of data suppliers and consumers. By staking tokens ($PYTH) and becoming data providers, delegators, or curators, users can provide data to Pyth. When there is a demand for data, users need to pay a certain amount of tokens, and the data providers can earn token rewards. Conversely, if the data source provides incorrect prices or if delegators and curators select data with poor quality, they will be penalized. Typically, the corresponding amount will be deducted from their staked tokens as compensation to the other party.

Advantages of Pyth

Rich data sources: Traditional oracles rely on third parties to run nodes and gather data from various sources. However, Pyth has over 90 professional data providers, covering more than 230 DApps and supporting over 40 mainnets. The data is directly obtained from these data institutions, and the institutions providing the data act as nodes for Pyth. This ensures real-time and high-fidelity data.

Price aggregation: Most traditional oracles aggregate prices offline and then upload them to the blockchain. However, Pyth directly aggregates prices on-chain, significantly reducing the time cost. Coupled with the low gas fees and high performance of the Solana network, Pyth’s price aggregation becomes more efficient.

Low latency and high frequency: In the oracle field, the speed of data updates is crucial. Pyth provides multiple price feeds per second, enabling high-frequency data updates that are faster than the block time of most blockchains. Pythnet is a fork of the Solana chain, and with the high-frequency updates of Pythnet off-chain, decentralized applications can use the latest off-chain price data in every transaction. Low latency allows each transaction to use the most recent off-chain price, rather than relying on the last on-chain update pushed by the oracle itself.

Data reliability and stability: Oracles may fail to update prices in unstable market conditions. In such cases, oracles would compete for bandwidth with more valuable transactions, such as DEX trades or settlements, and may often not afford the necessary fees for price updates. This problem does not occur in the Pull price update model, as Pyth’s price updates are integrated into valuable transactions themselves.

Latest Data From Pyth

The data since the deadline of this article is as follows:

• The number of Pyth Oracle price accounts in the past week is 890,000.

Source: https://dune.com/cctdaniel/pyth-oracle

• 15,778 daily active users in the past 24 hours, with a peak of 23,690 daily active users in the past month.

Source: https://dune.com/cctdaniel/pyth-oracle

Source: https://dune.com/cctdaniel/pyth-oracle

• 2,304,938 interactions by daily active users in the past 24 hours, with a peak of over 2,500,000 daily interactions in the past month.

Source: https://dune.com/cctdaniel/pyth-oracle

Source: https://dune.com/cctdaniel/pyth-oracle

Pyth vs Chainlink

As representatives of oracle systems, a comparison between Pyth and Chainlink is inevitable. The most obvious difference between Chainlink and Pyth lies in the fact that the former submits data on-chain, while the latter completes the process off-chain.

In terms of mechanisms, Chainlink’s system relies on third-party nodes to handle all price aggregation, oracle nodes, and price data sources. On the other hand, Pyth directly accomplishes price aggregation on-chain without the involvement of third parties. This aligns with Pyth’s pursuit of High-Fidelity, aiming for high-fidelity and lossless data. Although Chainlink can also choose to aggregate on-chain, the cost of submitting a price to the on-chain contract at each oracle node makes on-chain aggregation costly for the Chainlink network.

In terms of market share, Pyth still has a long way to go. As a leading project in the oracle sector, coupled with the first-mover advantage of its native token $Link, Chainlink currently holds the top position in the oracle market with a 52.97% share of the total oracle market value. Pyth, ranking fourth, only holds a 5.2% share. Of course, with the increasing demand and expectations for DeFi derivatives in the market, Pyth still has significant room for development.

Source: https://defillama.com/oracles

$PYTH Tokenomics

The design and mechanism of the $PYTH token aim to make the Pyth network self-sustaining and decentralized.

Source: https://pyth.network/whitepaper_v2.pdf?ref=pyth-network.ghost.io

$PYTH Token Allocation

• Maximum Supply: 10,000,000,000
• Initial Circulating Supply:1,500,000,000 (15%)
• Data Publisher Rewards: 22%
• Ecosystem Growth: 52%
• Protocol Development: 10%
• Community and Launch: 6% (All unlocked)
• Private Sale: 10% (All locked)
• Lockup Period: 85% of $PYTH tokens are initially locked and will gradually unlock after 6 months, 18 months, 30 months, and 42 months from the initial token launch.

$PYTH has received investments from institutions such as Delphi Digital, Alliance Dao, GBV Capital, Republic Capital, HTX Venture, KuCoin Labs, Ryze Labs, with a current market cap exceeding 800 million USD.

The Pyth Network token $PYTH has been launched, and 255 million tokens have been airdropped. The airdrop claiming window opened on November 20, 2023, at 2 PM UTC, and will continue until February 18, 2024, at 2 PM UTC. You can check if you qualify for the airdrop at https://airdrop.pyth.network/.

$PYTH is still in its early stages since its recent launch, and with the development of the Pyth Network, the token has significant potential for growth. Currently, the market cap of $PYTH is approximately 800 million USD, while Chainlink’s circulating market cap is fifteen times that of $PYTH, indicating substantial potential for upward movement. It is considered an early-stage oracle project worth investing in.

How to Acquire $PYTH Tokens?

To obtain $PYTH tokens and participate in the Pyth Network, you can purchase them through cryptocurrency exchanges. Reputable exchanges such as Gate.io support the purchase of $PYTH. Simply create a Gate.io account, complete the KYC process, and then deposit funds into your account to directly purchase $PYTH tokens.

Conclusion

With the continuous growth of the DeFi market capital, the demand for accurate and efficient DeFi data in the market is also increasing, so there is considerable room for development in the oracle track in the future. From the background of Pyth, we can also see that more and more traditional financial institutions are entering the crypto market, and the core competitiveness of Pyth will become increasingly prominent.