$PYTH project research analysis report

Intermediate2/10/2024, 9:48:52 AM
Pyth Network is a Solana-like version of Chainlink that provides price data oracles and market data to blockchain projects. This article is a comprehensive interpretation of Pyth Network.

1. Key points of the research report

1.1 Investment logic

Pyth Network, as a Solana version of Chainlink, provides price data oracles and market data to blockchain projects. It provides “mission-critical grade” price data for various asset classes such as cryptocurrencies, FX, commodities and equities, in a secure and zero-latency manner.

  • Pyth Network currently offers over 350 different data sources from exchanges such as Cboe Global Markets, Jane Street, CMS, Binance OKX, Two Sigma and many more. PYTH tokens are used for staking and governance within the Pyth Network, creating strong demand potential for stakeholders looking to influence the future direction of the protocol.
  • The background of the team is basically from Jump Trading, and they have certain attributes of pulling high-multiply coins.

1.2 Valuation description

Currently, Chainlink’s FDV is discounted by 0.95% compared to the total secured value (the total value of assets in the protocols served by its oracles). If you consider the same metrics, Pyth’s total guaranteed value is $2.121 billion, then the fair FDV is 2.121B * 0.95, or around $2.014 billion.

$PYTH has 15% of the circulating supply in TGE, giving it a market capitalization currently approaching $600 million, but at a fair price of $0.3. A price above $0.3 would make $PYTH overvalued based on on-chain demand. Consider the future potential of Python. Therefore, a fair 2–3x premium is reasonable, around $0.7–0.9. Buying $PYTH below $0.25 (currently as low as US$0.22) has a lot of room to multiply, and if it trades above $0.70, it may not be a good time right now.

In the long run, Pyth Network has good potential, and Pyth has some differentiated advantages over Chainlink to capture a good market share.

1.3 Main risks

Data provision market is saturated

The data provision market is currently very saturated, and the Pyth network can only provide price information, making the amount of data it can potentially provide far less than its competitors. While the fact that Python also provides confidence intervals may make it stand out a little, other data providers are fully capable of adding this functionality.

Provides malicious data risk

Pyth mainly uses data aggregators to prevent publishers from providing malicious data. (Permitted publishers can upload data for free).

Pyth Network has experienced data errors that saw Bitcoin prices skew significantly on its platform, leading to market instability. At the same time, the project is initially based on Solana and may face the limitations and risks of a single blockchain infrastructure.

Python fee structure

Pyth’s payment structure follows the “volunteer dilemma” model in game theory: that is, only when nodes cooperate with each other and jointly publish accurate data, each data update node can obtain the maximum token reward.

If users are required to pay individually to update information and can only access this information after paying, they may actually be more inclined to pay. However, users may actually be very reluctant to pay, or at least wait for the information to be updated, due to the potential for free prostitution.

2. Basic situation of the project

Pyth Network is a next-generation price oracle solution developed by Douro Labs, aiming to provide valuable financial market data on the chain, including cryptocurrencies, stocks, foreign exchange and commodities, etc., to projects and protocols and the public through blockchain technology. Pyth Network collects primary data from over 90 trusted data providers, including well-known exchanges, market makers, and financial institutions, and makes it available for use by smart contracts and other on-chain or off-chain applications.

2.1 Business scope

Pyth Network’s data business covers a wide range of asset classes, including cryptocurrencies, stocks, foreign exchange, ETFs, commodities and other asset classes. There are 250+ applications that trust Pyth data, including DEX, lending protocols and derivatives platforms.

At the same time, Pyth Network is not limited to specific blockchains. There are already 45+ blockchains actively receiving Pyth real-time market data to power their DeFi ecosystem. With over 80 million updates every day, Python allows your smart contracts to operate more accurately and securely.

After more than 400 data sources complete price publishing and data aggregation in Pythnet (Pyth application chain), price updates will be transmitted across chains through Wormhole, thereby extending the price data of assets to dozens of blockchains

2.2 Founding Team

CEO:Michael Cahill

CEO of Python development company Douro Labs. Previously, he worked on special projects at Jump Crypto.

COO:Ciaran Cronin

Ciaran Cronin is COO of Douro Labs, a pyth network development company, and previously worked at Jump Trading. He holds an MA in Financial Economics from University College Cork.

CTO:Jayant Krishnamurthy

Jayant Krishnamurthy is the CTO of Python development company Douro Labs and a software engineer at Jump Trading. He holds a PhD in computer science from Carnegie Mellon University.

CIO:Harnaik Kalirai

Chief Integration Officer, former Chief Integration Officer of Jump Trading, with many years of experience in system integration and operations, graduated from De Montfort University in the UK.

In addition, it is understood that in addition to the above-mentioned core executives, Jump Trading team members are also currently the most important code contributors to Pyth:

Jeff Schroeder: Technical director of Jump Trading, mainly responsible for the core code of Pyth;

Samir Islam: Technical Director of Jump Trading, Master of Computer Science from Oxford University, participated in Pyth code work;

Evan Gray: Vice President of Engineering at Jump Trading, involved in Pyth code work;

Alex Davies: Director of Product Development at Jump Trading, one of the first 10 employees of Jump Trading’s European division, also participated in the Pyth code work.

2.3 Investment background

Rootdata disclosed that Pyth has received investment from Delphi digital, Ailliance Dao, GBV Capital, Republic Capital, HTX Venture, KuCoin Labs, Ryze Labs and other institutions, and its current market value exceeds US$500 million. It is worth noting that PYTH also received a 40,000 OP grant from the OP Foundation.

In order to support the development of Pyth, the Switzerland-based Pyth Data Association was born. Its members include heavyweight institutions on Wall Street, such as Jump, SBF’s old owner Jane Street Capital, SIG and market maker Virtu Financial.

2.4 Project development route and history

Phase 1: Completed

  • Covers hard-to-get off-chain data as well as easily comparable on-chain data, including US stocks, cryptocurrencies, price + confidence intervals, market condition signals, TWAP, advanced aggregation portfolio methods;
  • Partner with companies that have access to unique data sources and want to put that data on the blockchain;
  • Broadcast raw data to Solana and distribute to other L1s and L2s;
  • Work with a small set of dApps on all available L1 and L2;
  • Partner with strategic DeFi ecosystems;
  • Launch the website. •Version 0.1;
  • Launch various social media community channels;

Phase 2: In Progress

  • Increase dataset coverage by adding futures and FX, extending TWAP and adding volatility and other data indicators;
  • Add data providers;
  • Increase integration;
  • Added Tier 1 support;
  • Mainnet online;
  • Launch staking, reward and management functions;

Phase 3: Coming soon

  • Dataset coverage increased for international stocks and futures;
  • Add data providers;
  • Increase integration;
  • Added Tier 1 support;
  • Introduce on-chain random numbers;
  • introducing fees and cuts;

3. Products and operations

3.1 Code and products

Pyth development activity on GitHub:

  • The Pyth Network’s main repository, named pythnet, shows a certain number of branches and stars, indicating a certain level of community involvement. The presence of code updates, issues, and pull requests indicates that development work is ongoing;
  • On their GitHub overview page, you can see that Pyth Network has multiple repositories, including pyth-client and pyth-client-js. Among them, the pyth-client repository, which contains the client API of the Pyth program on the chain, has received more attention than other repositories, which shows that the community is particularly interested in the client API aspect of Pyth Network;
  • The pyth-client` repository itself has active issue areas and pull requests, as well as actions for security and insights, which is further confirmation that the code base is undergoing continuous development and maintenance;
  • Additional documentation on Pyth Network’s integration with the EVM (Ethereum Virtual Machine) suggests that they are also focused on providing live data to EVM contracts, which may reflect broader development efforts beyond the direct repository;

The information provided shows that Pyth Network has a certain degree of development activities on GitHub, especially areas such as client APIs that have received more attention from developers.

The core components of Python

Pyth consists of three core parts: data providers (mainly exchanges), the Pyth protocol (designed to aggregate data from different providers to create uniform prices and confidence intervals for each price source every 400 milliseconds) and data consumers ( i.e. end users, such as applications on a Pyth-powered blockchain, read the aggregated price feed and seamlessly integrate the data into their smart contract logic).

The core mechanism of Python

Pyth core mechanism Pull price update model - Pyth Network uses a price update model that is different from other oracles. The Pull price update model is also the basis for the efficiency and fidelity of its data updates.

At present, most oracle machines adopt a push model. The oracle machine runs a process off-chain and continuously sends transactions to update the price on the chain. In contrast, Pyth Network does not have this process of pushing from off-chain to on-chain, but instead This task is delegated to users of the Pyth Network.

Pyth price updates are also created on the Pyth Network and transmitted off-chain via the Wormhole network. These updates are signed so that Pyth on-chain programs can verify their authenticity. To update the price on the chain, anyone can submit a verified update message to the Pyth contract, which is a permissionless operation. Typically, users using Pyth Network prices will submit a transaction that both updates the price and uses the price in downstream applications.

It’s important to note that on-chain prices can only move forward in time. If the user submits a wormhole message with a newer price, the Python program will not fail, but it will not update the price. This means that when a user automatically updates prices and interacts with a Pyth-driven application, there is no guarantee that the price read by the application is equal to the price submitted by the user.

Python workflow

Python is a protocol that allows market participants to publish pricing information on-chain for others to use. Data providers submit pricing information to a Pyth oracle program. ,Pyth provides multiple data providers for each price ,source to increase the accuracy and robustness of the ,system. The Pyth on-chain oracle program on Pythnet combines data submitted by providers to generate a single total price and confidence interval. The application reads the price information generated by the oracle program. More specifically, Python allows users to “pull” prices onto the blockchain when needed. (These prices are public to everyone on the chain)

  • After obtaining the price from the data agency, in order to ensure the security and credibility of the data, the data will also be estimated by Pyth’s own “confidence interval” to estimate the value range. For example, if the current price of ETH is 3,000 US dollars, then Pyth will calculate a price of about ±30 US dollars and provide an error range. The smaller the range, the higher the accuracy, and it can also give users a good reference.
  • Enter the Delegators. After receiving data from various institutions, Pyth relies on existing data sources plus historical performance and historical data accuracy to judge the quality of the data source and decide which data to use as Pyth’s data provider.
  • Curators and principals are both executed on the Solana network. The main role of curators is to screen what data is needed in the market and provide the data that is urgently needed.
  • Price aggregation is then performed via Pyth’s own “confidence intervals”. For example, one data source provides a price of $101±1 USD, while another publisher reports a price of $110±10 USD. In these cases, Pyth expects the total price to be closer to $101 than $110, and the overall confidence interval should reflect the variation between publisher prices.
  • After completing the price aggregation, if you continue to operate on the Solana network, you do not need to use Wormhole. On the contrary, if the subsequent operations are not performed on the Solana chain, you need the Layer1 cross-chain bridge function of Pyth and Wormhole to make the oracle data of Pyth available. Available to all chains.

In addition, Pyth uses reward and punishment mechanisms to guide the behavior of both data supply and demand parties. The pledge token ($PYTH) becomes a data provider, delegator (Delegators) or curator (Curators), and provides data to Pyth. When the user has data needs, he will pay a certain amount of tokens, and the data provider will You can get token rewards. On the contrary, when the data source provides a price error or the entruster or curator has a price error when screening the data quality, he or she will be punished. Generally, the corresponding amount will be deducted from the pledged token and given to the other party as compensation.

3.2 Official website data

The time range is October to December 2023:

  • Monthly visits: 1.479M (i.e. 1.479 million times)
  • Visit duration: Average visit duration is 3 minutes 44 minutes
  • Number of pages/visits: 3.82 pages viewed per visit on average

In addition, access traffic mainly comes from Indonesia 26.42%, Saudi Arabia 14.06%, and Argentina 9.86%, of which direct access accounts for 49.70% and natural search accounts for 22.29%

3.3 Social media data

3.4 Social data

3.5 Market popularity (promotion data and effects)

Sentiment indicator: 16.67, indicating that market sentiment is relatively positive.

Twitter discussion volume: 30, an increase of 1,400.00% from the previous period.

Number of Twitter followers: 167,500, an increase of 0.53% from the previous period.

The sentiment indicator’s tick marks range from -100 (very negative) to 100 (very positive), and the current indicator is showing at 16.67, which means the sentiment is biased toward the positive. In the past year, the growth trend of daily active users and user interactions has also increased significantly.

3.6 Partners

The Publishers projects on the Pyth network include:

Pyth Network is currently the largest primary financial data oracle network, supporting real-time price feeding services from more than 90 various data suppliers such as traditional financial institutions, crypto markets, foreign exchange, and commodities. Pyth supports data from over 40 top institutions in traditional financial and crypto markets, such as Bloomberg, Hong Kong Stock Exchange, Nasdaq, Jump Trading, Virtu Financial, GTS, and Solana.

4. Business analysis

4.1 Token model analysis

The maximum supply of PYTH tokens is 10 billion, and the initial circulation is 1.5 billion (15%). 85% of the total PYTH tokens are initially locked, and the locked tokens will be released on 6, 18, Unlocked at 30 and 42 months.

22% of this is allocated to network data providers; 52% is allocated to the “ecosystem growth strategy”; 10% is allocated to protocol development; 6% is reserved for the initial launch phase and related activities and plans; 10% allocation has been determined to be allocated to Two rounds of funding from strategic contributors.

It should be noted that in May 2024 - around the time of the next Bitcoin halving, a considerable portion of the tokens will be released. Furthermore, with the exception of community and launch, all rewards will be released at the same rate and time (it is understood that the top 10 holders own 68.02% of the supply), which leaves a lot of uncertainty for secondary market investments.

4.2 Project potential

Under the traditional push model, the DeFi protocol is equivalent to signing a cooperation contract with the oracle, purchasing the oracle’s services on a subscription basis, and enjoying the price feed and push of data for a period of time. There must be off-chain negotiation links and time consumption.

Under Pyth’s current on-demand pull model, the cooperation between the protocol and the oracle appears to be more Web3-based: you don’t even need to contact Pyth’s business team offline, just through development documents and smart contract deployment. Complete the pulling of price data - contract triggering, gas payment, data pulling and use after pulling are all executed automatically, reflecting the characteristics of “permissionless” and “full chain”.

Pyth’s characteristics are more similar to Web3, which allows it to have a place in the encryption market and also has extremely high potential. However, this potential cannot be transformed immediately, nor is it determined by technology, but is dominated by the market.

4.3 Competitive Landscape


Pyth Network is currently considered the fourth largest oracle project with a total value locked (TVL) of $2.112 billion, behind Chainlink, WINkLink and Chronicle.

In terms of the number of networks served, Python ranks second, serving 144 networks, second only to Chainlink’s 353. The price of Pyth Network has been on an upward trend recently and is expected to reach new highs in the coming months.While the long-term forecast remains bullish, the price of Pyth Network ($PYTH) may take longer than expected to reach the $1 milestone.

All things considered, Pyth Network occupies an important position in the field of decentralized financial oracles with its fast and accurate data provision capabilities.While its partially centralized data source may attract some criticism, its technical advantages and market application prospects make it a project worth paying attention to.

4.4 Earnings Expectation Assessment

Currently, Chainlink’s FDV is discounted by 0.95% compared to the total secured value (the total value of assets in the protocols served by its oracles).

If you consider the same metrics, Pyth’s total guaranteed value is $2.121 billion, then the fair FDV is 2.121B * 0.95, or around $2.014 billion.

$PYTH has 15% of the circulating supply in TGE, giving it a market capitalization currently approaching $600 million, but at a fair price of $0.3. A price above $0.3 would make $PYTH overvalued based on on-chain demand.

But we are now in a bull market cycle, given the future potential of Pyth. Therefore, a fair 2–3x premium is reasonable, around $0.7–0.9.

Buying $PYTH below $0.25 (currently as low as US$0.22) has a lot of room to multiply, and if it trades above $0.70, it may not be a good time right now.

In the long run, Pyth Network has good potential, and Pyth has some differentiated advantages over Chainlink to capture a good market share.

5. Summary & Suggestions

As the DeFi field continues to grow, the demand for reliable and real-time market data is also increasing. It can increase its market share by expanding to other asset classes such as stocks and commodities, break away from the binding with Solana, and build its own Python. Giving the project more flexibility, integration with other blockchain protocols and platforms can increase the usage scenarios and value of its data products.

As the global regulatory environment changes, there may be more regulatory requirements for on-chain data providers. As an infrastructure component, Pyth Network needs to ensure high security standards to resist potential network attacks. Any significant issues with data accuracy could quickly erode trust in its services.

The $PYTH token not only serves as fuel for transactions (i.e. pays gas fees), but also allows holders to share in network revenue and participate in governance decisions, but projects like Pyth dedicated to infrastructure construction are not as eye-catching as the oracles. The track is too narrow, and with ChainLink already in the lead, it will be difficult for Pyth to seize its share in a short period of time, but Pyth tokens are likely to grow 4–6 times in the new cycle.

Disclaimer:

  1. This article is reprinted from [medium]. All copyrights belong to the original author [密客资本]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
  2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.
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$PYTH project research analysis report

Intermediate2/10/2024, 9:48:52 AM
Pyth Network is a Solana-like version of Chainlink that provides price data oracles and market data to blockchain projects. This article is a comprehensive interpretation of Pyth Network.

1. Key points of the research report

1.1 Investment logic

Pyth Network, as a Solana version of Chainlink, provides price data oracles and market data to blockchain projects. It provides “mission-critical grade” price data for various asset classes such as cryptocurrencies, FX, commodities and equities, in a secure and zero-latency manner.

  • Pyth Network currently offers over 350 different data sources from exchanges such as Cboe Global Markets, Jane Street, CMS, Binance OKX, Two Sigma and many more. PYTH tokens are used for staking and governance within the Pyth Network, creating strong demand potential for stakeholders looking to influence the future direction of the protocol.
  • The background of the team is basically from Jump Trading, and they have certain attributes of pulling high-multiply coins.

1.2 Valuation description

Currently, Chainlink’s FDV is discounted by 0.95% compared to the total secured value (the total value of assets in the protocols served by its oracles). If you consider the same metrics, Pyth’s total guaranteed value is $2.121 billion, then the fair FDV is 2.121B * 0.95, or around $2.014 billion.

$PYTH has 15% of the circulating supply in TGE, giving it a market capitalization currently approaching $600 million, but at a fair price of $0.3. A price above $0.3 would make $PYTH overvalued based on on-chain demand. Consider the future potential of Python. Therefore, a fair 2–3x premium is reasonable, around $0.7–0.9. Buying $PYTH below $0.25 (currently as low as US$0.22) has a lot of room to multiply, and if it trades above $0.70, it may not be a good time right now.

In the long run, Pyth Network has good potential, and Pyth has some differentiated advantages over Chainlink to capture a good market share.

1.3 Main risks

Data provision market is saturated

The data provision market is currently very saturated, and the Pyth network can only provide price information, making the amount of data it can potentially provide far less than its competitors. While the fact that Python also provides confidence intervals may make it stand out a little, other data providers are fully capable of adding this functionality.

Provides malicious data risk

Pyth mainly uses data aggregators to prevent publishers from providing malicious data. (Permitted publishers can upload data for free).

Pyth Network has experienced data errors that saw Bitcoin prices skew significantly on its platform, leading to market instability. At the same time, the project is initially based on Solana and may face the limitations and risks of a single blockchain infrastructure.

Python fee structure

Pyth’s payment structure follows the “volunteer dilemma” model in game theory: that is, only when nodes cooperate with each other and jointly publish accurate data, each data update node can obtain the maximum token reward.

If users are required to pay individually to update information and can only access this information after paying, they may actually be more inclined to pay. However, users may actually be very reluctant to pay, or at least wait for the information to be updated, due to the potential for free prostitution.

2. Basic situation of the project

Pyth Network is a next-generation price oracle solution developed by Douro Labs, aiming to provide valuable financial market data on the chain, including cryptocurrencies, stocks, foreign exchange and commodities, etc., to projects and protocols and the public through blockchain technology. Pyth Network collects primary data from over 90 trusted data providers, including well-known exchanges, market makers, and financial institutions, and makes it available for use by smart contracts and other on-chain or off-chain applications.

2.1 Business scope

Pyth Network’s data business covers a wide range of asset classes, including cryptocurrencies, stocks, foreign exchange, ETFs, commodities and other asset classes. There are 250+ applications that trust Pyth data, including DEX, lending protocols and derivatives platforms.

At the same time, Pyth Network is not limited to specific blockchains. There are already 45+ blockchains actively receiving Pyth real-time market data to power their DeFi ecosystem. With over 80 million updates every day, Python allows your smart contracts to operate more accurately and securely.

After more than 400 data sources complete price publishing and data aggregation in Pythnet (Pyth application chain), price updates will be transmitted across chains through Wormhole, thereby extending the price data of assets to dozens of blockchains

2.2 Founding Team

CEO:Michael Cahill

CEO of Python development company Douro Labs. Previously, he worked on special projects at Jump Crypto.

COO:Ciaran Cronin

Ciaran Cronin is COO of Douro Labs, a pyth network development company, and previously worked at Jump Trading. He holds an MA in Financial Economics from University College Cork.

CTO:Jayant Krishnamurthy

Jayant Krishnamurthy is the CTO of Python development company Douro Labs and a software engineer at Jump Trading. He holds a PhD in computer science from Carnegie Mellon University.

CIO:Harnaik Kalirai

Chief Integration Officer, former Chief Integration Officer of Jump Trading, with many years of experience in system integration and operations, graduated from De Montfort University in the UK.

In addition, it is understood that in addition to the above-mentioned core executives, Jump Trading team members are also currently the most important code contributors to Pyth:

Jeff Schroeder: Technical director of Jump Trading, mainly responsible for the core code of Pyth;

Samir Islam: Technical Director of Jump Trading, Master of Computer Science from Oxford University, participated in Pyth code work;

Evan Gray: Vice President of Engineering at Jump Trading, involved in Pyth code work;

Alex Davies: Director of Product Development at Jump Trading, one of the first 10 employees of Jump Trading’s European division, also participated in the Pyth code work.

2.3 Investment background

Rootdata disclosed that Pyth has received investment from Delphi digital, Ailliance Dao, GBV Capital, Republic Capital, HTX Venture, KuCoin Labs, Ryze Labs and other institutions, and its current market value exceeds US$500 million. It is worth noting that PYTH also received a 40,000 OP grant from the OP Foundation.

In order to support the development of Pyth, the Switzerland-based Pyth Data Association was born. Its members include heavyweight institutions on Wall Street, such as Jump, SBF’s old owner Jane Street Capital, SIG and market maker Virtu Financial.

2.4 Project development route and history

Phase 1: Completed

  • Covers hard-to-get off-chain data as well as easily comparable on-chain data, including US stocks, cryptocurrencies, price + confidence intervals, market condition signals, TWAP, advanced aggregation portfolio methods;
  • Partner with companies that have access to unique data sources and want to put that data on the blockchain;
  • Broadcast raw data to Solana and distribute to other L1s and L2s;
  • Work with a small set of dApps on all available L1 and L2;
  • Partner with strategic DeFi ecosystems;
  • Launch the website. •Version 0.1;
  • Launch various social media community channels;

Phase 2: In Progress

  • Increase dataset coverage by adding futures and FX, extending TWAP and adding volatility and other data indicators;
  • Add data providers;
  • Increase integration;
  • Added Tier 1 support;
  • Mainnet online;
  • Launch staking, reward and management functions;

Phase 3: Coming soon

  • Dataset coverage increased for international stocks and futures;
  • Add data providers;
  • Increase integration;
  • Added Tier 1 support;
  • Introduce on-chain random numbers;
  • introducing fees and cuts;

3. Products and operations

3.1 Code and products

Pyth development activity on GitHub:

  • The Pyth Network’s main repository, named pythnet, shows a certain number of branches and stars, indicating a certain level of community involvement. The presence of code updates, issues, and pull requests indicates that development work is ongoing;
  • On their GitHub overview page, you can see that Pyth Network has multiple repositories, including pyth-client and pyth-client-js. Among them, the pyth-client repository, which contains the client API of the Pyth program on the chain, has received more attention than other repositories, which shows that the community is particularly interested in the client API aspect of Pyth Network;
  • The pyth-client` repository itself has active issue areas and pull requests, as well as actions for security and insights, which is further confirmation that the code base is undergoing continuous development and maintenance;
  • Additional documentation on Pyth Network’s integration with the EVM (Ethereum Virtual Machine) suggests that they are also focused on providing live data to EVM contracts, which may reflect broader development efforts beyond the direct repository;

The information provided shows that Pyth Network has a certain degree of development activities on GitHub, especially areas such as client APIs that have received more attention from developers.

The core components of Python

Pyth consists of three core parts: data providers (mainly exchanges), the Pyth protocol (designed to aggregate data from different providers to create uniform prices and confidence intervals for each price source every 400 milliseconds) and data consumers ( i.e. end users, such as applications on a Pyth-powered blockchain, read the aggregated price feed and seamlessly integrate the data into their smart contract logic).

The core mechanism of Python

Pyth core mechanism Pull price update model - Pyth Network uses a price update model that is different from other oracles. The Pull price update model is also the basis for the efficiency and fidelity of its data updates.

At present, most oracle machines adopt a push model. The oracle machine runs a process off-chain and continuously sends transactions to update the price on the chain. In contrast, Pyth Network does not have this process of pushing from off-chain to on-chain, but instead This task is delegated to users of the Pyth Network.

Pyth price updates are also created on the Pyth Network and transmitted off-chain via the Wormhole network. These updates are signed so that Pyth on-chain programs can verify their authenticity. To update the price on the chain, anyone can submit a verified update message to the Pyth contract, which is a permissionless operation. Typically, users using Pyth Network prices will submit a transaction that both updates the price and uses the price in downstream applications.

It’s important to note that on-chain prices can only move forward in time. If the user submits a wormhole message with a newer price, the Python program will not fail, but it will not update the price. This means that when a user automatically updates prices and interacts with a Pyth-driven application, there is no guarantee that the price read by the application is equal to the price submitted by the user.

Python workflow

Python is a protocol that allows market participants to publish pricing information on-chain for others to use. Data providers submit pricing information to a Pyth oracle program. ,Pyth provides multiple data providers for each price ,source to increase the accuracy and robustness of the ,system. The Pyth on-chain oracle program on Pythnet combines data submitted by providers to generate a single total price and confidence interval. The application reads the price information generated by the oracle program. More specifically, Python allows users to “pull” prices onto the blockchain when needed. (These prices are public to everyone on the chain)

  • After obtaining the price from the data agency, in order to ensure the security and credibility of the data, the data will also be estimated by Pyth’s own “confidence interval” to estimate the value range. For example, if the current price of ETH is 3,000 US dollars, then Pyth will calculate a price of about ±30 US dollars and provide an error range. The smaller the range, the higher the accuracy, and it can also give users a good reference.
  • Enter the Delegators. After receiving data from various institutions, Pyth relies on existing data sources plus historical performance and historical data accuracy to judge the quality of the data source and decide which data to use as Pyth’s data provider.
  • Curators and principals are both executed on the Solana network. The main role of curators is to screen what data is needed in the market and provide the data that is urgently needed.
  • Price aggregation is then performed via Pyth’s own “confidence intervals”. For example, one data source provides a price of $101±1 USD, while another publisher reports a price of $110±10 USD. In these cases, Pyth expects the total price to be closer to $101 than $110, and the overall confidence interval should reflect the variation between publisher prices.
  • After completing the price aggregation, if you continue to operate on the Solana network, you do not need to use Wormhole. On the contrary, if the subsequent operations are not performed on the Solana chain, you need the Layer1 cross-chain bridge function of Pyth and Wormhole to make the oracle data of Pyth available. Available to all chains.

In addition, Pyth uses reward and punishment mechanisms to guide the behavior of both data supply and demand parties. The pledge token ($PYTH) becomes a data provider, delegator (Delegators) or curator (Curators), and provides data to Pyth. When the user has data needs, he will pay a certain amount of tokens, and the data provider will You can get token rewards. On the contrary, when the data source provides a price error or the entruster or curator has a price error when screening the data quality, he or she will be punished. Generally, the corresponding amount will be deducted from the pledged token and given to the other party as compensation.

3.2 Official website data

The time range is October to December 2023:

  • Monthly visits: 1.479M (i.e. 1.479 million times)
  • Visit duration: Average visit duration is 3 minutes 44 minutes
  • Number of pages/visits: 3.82 pages viewed per visit on average

In addition, access traffic mainly comes from Indonesia 26.42%, Saudi Arabia 14.06%, and Argentina 9.86%, of which direct access accounts for 49.70% and natural search accounts for 22.29%

3.3 Social media data

3.4 Social data

3.5 Market popularity (promotion data and effects)

Sentiment indicator: 16.67, indicating that market sentiment is relatively positive.

Twitter discussion volume: 30, an increase of 1,400.00% from the previous period.

Number of Twitter followers: 167,500, an increase of 0.53% from the previous period.

The sentiment indicator’s tick marks range from -100 (very negative) to 100 (very positive), and the current indicator is showing at 16.67, which means the sentiment is biased toward the positive. In the past year, the growth trend of daily active users and user interactions has also increased significantly.

3.6 Partners

The Publishers projects on the Pyth network include:

Pyth Network is currently the largest primary financial data oracle network, supporting real-time price feeding services from more than 90 various data suppliers such as traditional financial institutions, crypto markets, foreign exchange, and commodities. Pyth supports data from over 40 top institutions in traditional financial and crypto markets, such as Bloomberg, Hong Kong Stock Exchange, Nasdaq, Jump Trading, Virtu Financial, GTS, and Solana.

4. Business analysis

4.1 Token model analysis

The maximum supply of PYTH tokens is 10 billion, and the initial circulation is 1.5 billion (15%). 85% of the total PYTH tokens are initially locked, and the locked tokens will be released on 6, 18, Unlocked at 30 and 42 months.

22% of this is allocated to network data providers; 52% is allocated to the “ecosystem growth strategy”; 10% is allocated to protocol development; 6% is reserved for the initial launch phase and related activities and plans; 10% allocation has been determined to be allocated to Two rounds of funding from strategic contributors.

It should be noted that in May 2024 - around the time of the next Bitcoin halving, a considerable portion of the tokens will be released. Furthermore, with the exception of community and launch, all rewards will be released at the same rate and time (it is understood that the top 10 holders own 68.02% of the supply), which leaves a lot of uncertainty for secondary market investments.

4.2 Project potential

Under the traditional push model, the DeFi protocol is equivalent to signing a cooperation contract with the oracle, purchasing the oracle’s services on a subscription basis, and enjoying the price feed and push of data for a period of time. There must be off-chain negotiation links and time consumption.

Under Pyth’s current on-demand pull model, the cooperation between the protocol and the oracle appears to be more Web3-based: you don’t even need to contact Pyth’s business team offline, just through development documents and smart contract deployment. Complete the pulling of price data - contract triggering, gas payment, data pulling and use after pulling are all executed automatically, reflecting the characteristics of “permissionless” and “full chain”.

Pyth’s characteristics are more similar to Web3, which allows it to have a place in the encryption market and also has extremely high potential. However, this potential cannot be transformed immediately, nor is it determined by technology, but is dominated by the market.

4.3 Competitive Landscape


Pyth Network is currently considered the fourth largest oracle project with a total value locked (TVL) of $2.112 billion, behind Chainlink, WINkLink and Chronicle.

In terms of the number of networks served, Python ranks second, serving 144 networks, second only to Chainlink’s 353. The price of Pyth Network has been on an upward trend recently and is expected to reach new highs in the coming months.While the long-term forecast remains bullish, the price of Pyth Network ($PYTH) may take longer than expected to reach the $1 milestone.

All things considered, Pyth Network occupies an important position in the field of decentralized financial oracles with its fast and accurate data provision capabilities.While its partially centralized data source may attract some criticism, its technical advantages and market application prospects make it a project worth paying attention to.

4.4 Earnings Expectation Assessment

Currently, Chainlink’s FDV is discounted by 0.95% compared to the total secured value (the total value of assets in the protocols served by its oracles).

If you consider the same metrics, Pyth’s total guaranteed value is $2.121 billion, then the fair FDV is 2.121B * 0.95, or around $2.014 billion.

$PYTH has 15% of the circulating supply in TGE, giving it a market capitalization currently approaching $600 million, but at a fair price of $0.3. A price above $0.3 would make $PYTH overvalued based on on-chain demand.

But we are now in a bull market cycle, given the future potential of Pyth. Therefore, a fair 2–3x premium is reasonable, around $0.7–0.9.

Buying $PYTH below $0.25 (currently as low as US$0.22) has a lot of room to multiply, and if it trades above $0.70, it may not be a good time right now.

In the long run, Pyth Network has good potential, and Pyth has some differentiated advantages over Chainlink to capture a good market share.

5. Summary & Suggestions

As the DeFi field continues to grow, the demand for reliable and real-time market data is also increasing. It can increase its market share by expanding to other asset classes such as stocks and commodities, break away from the binding with Solana, and build its own Python. Giving the project more flexibility, integration with other blockchain protocols and platforms can increase the usage scenarios and value of its data products.

As the global regulatory environment changes, there may be more regulatory requirements for on-chain data providers. As an infrastructure component, Pyth Network needs to ensure high security standards to resist potential network attacks. Any significant issues with data accuracy could quickly erode trust in its services.

The $PYTH token not only serves as fuel for transactions (i.e. pays gas fees), but also allows holders to share in network revenue and participate in governance decisions, but projects like Pyth dedicated to infrastructure construction are not as eye-catching as the oracles. The track is too narrow, and with ChainLink already in the lead, it will be difficult for Pyth to seize its share in a short period of time, but Pyth tokens are likely to grow 4–6 times in the new cycle.

Disclaimer:

  1. This article is reprinted from [medium]. All copyrights belong to the original author [密客资本]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
  2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.
  3. Translations of the article into other languages are done by the Gate Learn team. Unless mentioned, copying, distributing, or plagiarizing the translated articles is prohibited.
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